Identifying ambiguous cardiac signals for electrophysiologic mapping

ABSTRACT

A system and associated method is disclosed for determining whether a signal is ambiguous. The system comprises an electrode apparatus comprising a plurality of electrodes configured to be located proximate tissue of a patient. A display apparatus comprises a graphical user interface. The graphical user interface is configured to present information to a user. A computing apparatus coupled to the electrode apparatus and display apparatus, is configured to determine whether a signal acquired from a channel associated with an electrode from the plurality of electrodes is ambiguous. The computing apparatus is configured to calculate a first derivative of the signal, determine a first minimum from the first derivative, determine a second minimum from the second derivative and a second index within a window, calculate a ratio of the first and second derivatives, calculate a difference between a first and second index. In response to determining the ratio and the difference between the first and second index, the display apparatus displays whether the signal is ambiguous.

RELATED APPLICATION

Cross-reference is hereby made to commonly assigned U.S. patentapplication Ser. No. ______, filed on even date herewith (AttorneyDocket Number C00008453.USU2) entitled “DETERMINING ONSET OF CARDIACDEPOLARIZATION AND REPOLARIZATION WAVES FOR SIGNAL PROCESSING”, U.S.patent application Ser. No. ______, filed on even date herewith(Attorney Docket Number C00008453.USU3) entitled “DETECTION OF VALIDSIGNALS VERSUS ARTIFACTS”, and incorporated by reference in theirentirety.

TECHNICAL FIELD

The present disclosure relates to medical devices, and moreparticularly, to medical devices for sensing, detection, and analysis ofcardiac signals.

BACKGROUND

Implantable medical devices (IMDs), such as implantable pacemakers,cardioverters, defibrillators, or pacemaker-cardioverter-defibrillators,provide therapeutic electrical stimulation to the heart. IMDs mayprovide pacing to address bradycardia, or pacing or shocks in order toterminate tachyarrhythmia, such as tachycardia or fibrillation. In somecases, the medical device may sense intrinsic depolarizations of theheart, detect arrhythmia based on the intrinsic depolarizations (orabsence thereof), and control delivery of electrical stimulation to theheart if arrhythmia is detected based on the intrinsic depolarizations.

IMDs may also provide cardiac resynchronization therapy (CRT), which isa form of pacing. CRT involves the delivery of pacing to the leftventricle, or both the left and right ventricles. The timing andlocation of the delivery of pacing pulses to the ventricle(s) may beselected to improve the coordination and efficiency of ventricularcontraction.

IMDs sense signals and deliver therapeutic stimulation via electrodes.Implantable pacemakers, cardioverters, defibrillators, orpacemaker-cardioverter-defibrillators are typically coupled to one ormore subcutaneous electrodes or intracardiac leads that carry electrodesfor cardiac sensing and delivery of therapeutic stimulation. The signalssensed via the electrodes may be referred to as a cardiac electrogram(EGM) and may include the depolarizations, repolarizations, and otherintrinsic electrical activity of the heart.

Systems for implanting medical devices may include workstations or otherequipment in addition to the medical device itself. In some cases, theseother pieces of equipment assist the physician or other technician withplacing the intracardiac leads at particular locations on the heart. Insome cases, the equipment provides information to the physician aboutthe electrical activity of the heart and the location of theintracardiac lead. The equipment may perform similar functions as themedical device, including delivering electrical stimulation to the heartand sensing the depolarizations of the heart. In some cases, theequipment may include equipment for obtaining an electrocardiogram (ECG)via skin electrodes placed on the surface of the patient. In addition,the patient may have a plurality of electrodes on an ECG belt or vestthat surrounds the torso of the patient. After the vest has been securedto the torso, a physician can perform a series of tests to evaluate apatient's cardiac response.

During the evaluation process, a physician typically needs to review theonset of cardiac depolarization waves in the rhythms using a computingapparatus. Numerous methods are used to detect onset of depolarizationwaves. U.S. Pat. No. 8,781,580B2 to Sven-Erik Hedberg et al. is directedto pacing sequence optimization applied through the multipolar LV leadbased on a particular optimization criterion which is the time point ofthe onset of activation of the left ventricle until closure of themitral valve of the heart. The pacing sequence that minimizes the timeinterval from onset of LV activation until the mitral valve closure isidentified and used as currently optimal pacing sequence for the IMD. Anactivation detector is configured to detect onset of activation of theleft ventricle for a cardiac cycle. The activation detector isconfigured to detect onset of contraction of the left ventricle for thecardiac cycle based on i) a signal received by the connector for aconnectable sensor or ii) an impedance signal determined by the activitydetector based on an electric signal received by the connector from aconnectable pacing electrode. Nowhere in this method does it eliminatepolarization artifacts to ensure the best channel is selected or adjustdetection of the onset of cardiac depolarization to ensure beats are notmissed.

Additionally, the Sven-Erik Hedberg method does not address ambiguouscardiac signals. U.S. Pat. No. 7,953,489 B2 to Warren et al. Warren etal does correct for ambiguous signals, defined as sensed cardiacelectrical signal that are difficult to comprehend, understand, orclassify by an implantable medical device (IMD) (e.g. ICD etc.) system'sdetection architecture. Warren et al. addresses ambiguous signals bycounting to characteristic features, comparing the ambiguous signal to athreshold, and then sensing alternate cardiac signals. This method canbe cumbersome since the characteristic features need to be parsed andcounted.

It is therefore desirable to develop additional methods and systems forsignal processing that allows the system to acquire cardiac signals withlittle or no artifacts and/or ambiguous signals thereby allowingphysicians to more accurately determine therapy for a patient.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating and example system that maydetermine the onsets and offsets of various heart repolarization anddepolarization waves.

FIG. 2 is a block diagram illustrating an example configuration of awave detection module.

FIG. 3 is a flow diagram for validating electrocardiograms (ECG) dataacquired from a plurality of channels and eliminating data that isdeemed invalid.

FIG. 4 is a graph illustrating an example cardiac ECG that shows invaliddata that is excluded by the method depicted in FIG. 3.

FIG. 5 is a graph illustrating an example linear step function thatshows invalid data that is excluded by the method depicted in FIG. 3.

FIG. 6 is a graph illustrating an example of a second derivative of anECG signal that is not equal to zero.

FIG. 7 is a flow diagram for detecting a signal that exhibits a strongfidelity of a signal.

FIG. 8 is a graph illustrating an example rectified ECG that shows onsetof a local depolarization waves determined by the method depicted inFIG. 7.

FIG. 9 is a graph illustrating an example of a rectified ECG that showsonset of two different local depolarization waves determined by themethod depicted in FIG. 7.

FIG. 10 is a flow diagram illustrating an example technique fordetermining beat information such as a maximum for each beat acquiredfrom a signal on a channel.

FIG. 11 is a graph illustrating a square of a first derivative of an ECGsignal that shows a set of local maximums associated with a set ofbeats.

FIG. 12 is a graph illustrating a square of a first derivative ofanother exemplary ECG signal that shows a set of local maximumsassociated with a set of beats.

FIG. 13 is a graph diagram an example two different local maximums inwhich the onset of heart depolarization has been determined afterperforming methods 100-300 depicted in FIGS. 3, 7 and 10.

FIG. 14 is a graph diagram of an example two different local maximums inwhich the onset of heart depolarization has been determined afterperforming methods 100-300 depicted in FIGS. 3, 7 and 10.

FIG. 15 is a conceptual diagram illustrating an example system thatdetermines the onset and offsets of heart depolarization andrepolarization waves.

FIGS. 16-17 are conceptual diagrams illustrating exemplary systems formeasuring torso-surface potentials.

FIG. 18 is a conceptual diagram illustrating the implantable medicaldevice (IMD) and leads of the system shown in FIG. 15 in greater detail.

FIG. 19 is a block diagram of an example implantable medical device thatmay determine the onset and offset of heart depolarization andrepolarization waves.

FIG. 20 is a graph compares invalid and valid ECG signals relative to athreshold employed for eliminating invalid signal data.

FIG. 21 is a diagram of an exemplary system including electrodeapparatus, imaging apparatus, display apparatus, and computingapparatus.

FIG. 22 is a schematic diagram depicting a maximum and several closelyspaced apart local maximums associated with a potentially valid signalas processed through block 324 of FIG. 7.

FIG. 23 is a schematic diagram depicting time index samples of localmaximums.

FIG. 24 depicts an acceptable onset of cardiac depolarization such thatthe square of the first derivative is smaller than 5% of the first localmaximum that was updated in FIG. 10.

FIG. 25 is a flow diagram for validating electrocardiograms (ECG) dataacquired from a plurality of channels and eliminating data that isdeemed invalid due to artifacts.

FIG. 26 graphically depicts an exemplary derivative of a signal.

FIG. 27 graphically depicts an exemplary derivative of an artifactsignal.

FIG. 28A graphically depicts a R waveform.

FIG. 28B graphically depicts a biphasic QRS waveform.

FIG. 28C graphically depicts a R-s waveform.

FIG. 28D graphically depicts a QS waveform.

FIG. 29 depicts a method for identifying ambiguous cardiac signalsduring electrophysiologic mapping.

FIG. 30 depicts an ECG signal acquired from a surface electrodeassociated with an electrode apparatus.

FIG. 31 depicts a derivative of the ECG signal from FIG. 30.

FIGS. 32 and 33 show exemplary signals with dashed lines intersecting ata steepest point of each curve.

FIG. 34 graphically depicts an ambiguous signal acquired from a surfaceelectrode associated with an electrode apparatus.

FIG. 35 depicts first local maximums amongst a set of local maximums.

SUMMARY

The present disclosure assists in eliminating ambiguous signalsassociated with cardiac signals acquired from one or more electrodesassociated with an electrode apparatus. By eliminating ambiguoussignals, techniques and methods described herein substantially increasethe accuracy of the onset of each heart depolarization over conventionalthreshold detection methods.

One or more embodiments relate to a system and associated method fordetermining whether a signal is ambiguous. The system comprises anelectrode apparatus comprising a plurality of electrodes configured tobe located proximate tissue of a patient. A display apparatus comprisesa graphical user interface. The graphical user interface is configuredto present information to a user. A computing apparatus coupled to theelectrode apparatus and display apparatus, is configured to determinewhether a signal acquired from a channel associated with an electrodefrom the plurality of electrodes is ambiguous. The computing apparatusis configured to calculate a first derivative of the signal, determine afirst minimum from the first derivative, determine a second minimum fromthe second derivative and a second index within a window, calculate aratio of the first and second derivatives, calculate a differencebetween a first and second index. In response to determining the ratioand the difference between the first and second index, the displayapparatus displays whether the signal is ambiguous.

DETAILED DESCRIPTION

Exemplary systems, methods, and interfaces shall be described withreference to FIGS. 1-35. It will be apparent to one skilled in the artthat elements or processes from one embodiment may be used incombination with elements or processes of the other embodiments, andthat the possible embodiments of such methods, apparatus, and systemsusing combinations of features set forth herein is not limited to thespecific embodiments shown in the Figures and/or described herein.Further, it will be recognized that the embodiments described herein mayinclude many elements that are not necessarily shown to scale. Stillfurther, it will be recognized that timing of the processes and the sizeand shape of various elements herein may be modified but still fallwithin the scope of the present disclosure, although certain timings,one or more shapes and/or sizes, or types of elements, may beadvantageous over others.

One or more embodiments of the present disclosure is embodied in methods100-300, depicted in FIGS. 3, 7, and 10, which ensures that the mostaccurate data acquired from an electrode apparatus is used to updateonset data for each beat. Accuracy of the onset data is improved byeliminating noise (e.g. artifacts) that can obscure signals.

One or more other embodiments depicted in FIGS. 25 and 29 areimplemented after the onset data has been updated. FIG. 25, for example,validates electrocardiograms (ECG) data acquired from a plurality ofchannels and eliminates data that is deemed invalid due to artifacts.FIG. 29 serves to identify ambiguous cardiac signals and locateschannels that provide non-ambiguous signals. The teachings of FIG. 29can also be applied to the signal processing techniques describedrelative to FIGS. 3, 7, and 10 and/or FIG. 25. Alternatively, FIG. 29can independently be applied to a cardiac signal without the processingtechniques FIGS. 3, 7, and 10 and/or FIG. 25 being used before or afterFIG. 29. The remaining diagrams depict the hardware and/or details as toimplementation of the methods described herein.

FIG. 1 is a block diagram illustrating an example configuration of asystem for determining the onsets and/or offsets of heart depolarizationand repolarizations waves. In the illustrated example, system 10includes a device 60, a cardiac electrogram module 70, and a motionsensing module 80. Device 60 may further include a processor 72, amemory 74, a peak detection module 76, and a wave detection module 78.

Processor 72 may include any one or more of a microprocessor, acontroller, a digital signal processor (DSP), an application specificintegrated circuit (ASIC), a field-programmable gate array (FPGA), orequivalent discrete or analog logic circuitry. In some examples,processor 72 may include multiple components, such as any combination ofone or more microprocessors, one or more controllers, one or more DSPs,one or more ASICs, or one or more FPGAs, as well as other discrete orintegrated logic circuitry. The functions attributed to processor 72herein may be embodied as software, firmware, hardware or anycombination thereof. Generally, processor 72 controls cardiacelectrogram module 70, peak detection module 76, wave detection module78, and motion sensing module 80 to determine timings of the onsets andoffsets of heart depolarization and/or repolarizations waves. Processor72 can perform calculations, determinations, comparisons of data etc.

In general, a heart produces a repetitive electrical signal which causesthe heart to mechanically contract, thereby pumping blood throughout thebody. Generally, the signal may be detected and displayed as a cardiacelectrogram signal. Although the exact representation may differdepending on the placement of leads on or within the body to detect theheart signal, among other factors, a common cardiac electrogram includesseveral recognizable features. The initial deflections of the signalrepresent the P-wave and the QRS complex. The P-wave represents thedepolarization of the atria and the QRS complex represents thedepolarization of the ventricles. The Q-wave of the QRS complex is theinitial downward deflection of the signal during the complex. Followingthe Q-wave is the R-wave, which is an upward deflection of the signal.Finally, the S-wave is another downward deflection. The next portion ofthe signal represents repolarization of the atria and ventricles. Morespecifically, what is generally called the T-wave represents therepolarization of the ventricles. There is no specific wave or featureof the signal that represents the repolarization of the atria becausethe generated signal is small in comparison to the T-wave. Together, theP-wave, the Q, R, and S waves, and the T-wave represent thedepolarization and repolarization waves of a heart electrical signal.

Memory 74 includes computer-readable instructions that, when executed byprocessor 72, causes system 10 and processor 72 to perform variousfunctions attributed to system 10 and processor 72 herein. Memory 74 mayinclude any volatile, non-volatile, magnetic, optical, or electricalmedia, such as a random access memory (RAM), read-only memory (ROM),non-volatile RAM (NVRAM), electrically-erasable programmable ROM(EEPROM), flash memory, or any other digital or analog media.

Generally, cardiac electrogram module 70 is configured sense or acquireelectrical signals from a patient. Cardiac electrogram module 70 iselectrically coupled to one or more electrodes 2, 4, 6, 8, 10, 12, 14 .. . n by one or more leads. In some examples, the one or more electrodes2, 4, 6, 8, 10, 12, 14 . . . n may be external electrodes, e.g.,attached to the surface of a patient, or implanted at various locationswithin a patient, e.g., on or within a heart.

Peak detection module 76 may be configured to determine a maximum valueof a particular signal. For example, peak detection module 76 may beconfigured to receive the electrical signal from cardiac electrogrammodule 70 and determine the maximum value. In another example, asillustrated in FIG. 2, peak detection module 76 may be configured toreceive a signal from wave detection module 78 and determine a maximumvalue.

Wave detection module 78 determines the onsets and/or offsets on theheart depolarization and repolarizations waves. Wave detection module 78may be configured to receive an electrical signal. For example, wavedetection module 78 may be configured to receive an electrical signalsensed by cardiac electrogram module 70. Motion sensing module 80 maydetect mechanical motion of a heart, e.g., during contraction of theheart. Motion sensing module 80 may comprise one or more sensors thatgenerate a signal that varies based on cardiac contraction or motiongenerally, such as one or more accelerometers, pressure sensors,impedance sensors, or flow sensors. Motion sensing module 80 may providean indication of the timing of motion, e.g., contraction, to device 60,e.g., to processor 72. The detected contraction may be contraction ofcardiac tissue at a particular location, e.g., a particular portion of aventricular wall.

In some examples, motion sensing module 80 may be configured to imagethe heart, or electrodes, catheters, wires, or other radio-opaquemarkers in or on the heart and identify motion associated withcontraction based on images of the heart. In some examples, motionsensing module 80 may be configured to direct ultrasound energy toward apatient's heart. Motion sensing module 80 may also be configured todetect any ultrasonic energy deflected back toward motion sensing module80 by the patient's heart. In this manner, motion sensing module 80 maycapture information about the mechanical motion (i.e. the contractingand relaxing of the ventricles and/or atria) of the heart. Systems andmethods for identifying heart mechanical contractions are described inU.S. Pat. No. 7,587,074 to Zarkh et al., which issued on Sep. 8, 2009and is entitled, “METHOD AND SYSTEM FOR IDENTIFYING OPTIMAL IMAGE WITHINA SERIES OF IMAGES THAT DEPICT A MOVING ORGAN,” and is incorporatedherein by reference in its entirety.

Processor 72 may determine values of one or more metrics, such ascardiac intervals or cardiac electromechanical delay, based on thetiming of onset and/or offset of a wave, as determined by wave detectionmodule 78, and/or the timing of contraction, as determined by motionsensing module 80. For example, processor 72 may determine QRS widthbased on an onset and offset of the QRS complex as identified by wavedetection module 78. As another example, processor 72 may determine a QTinterval based on a QRS onset and T-wave onset identified by wavedetection module 78. The processor may also determine the intervalbetween the onset of depolarization on a surface ECG lead and the timeof local electrical activation as sensed by a lead or a mapping catheteror guidewire at a site within the heart. Furthermore, as described ingreater detail below, processor 72 may determine electromechanical delaybased on a QRS onset identified by wave detection module 78 and anindication of the timing of cardiac contraction received from motionsensing module 80.

Although in FIG. 1 device 60, module 70, and module 80 are depicted asseparate, in other examples the modules and device may be combined intofewer separate components. For example, as illustrated in FIG. 13, allof the functionality of system 10 may be combined into a single device.

Furthermore, although processor 72, peak detection module 76 and wavedetection module 78 are depicted as separate functional modules in theexample of FIG. 1, their collective functionality may be provided by anynumber of physical or logical processing elements provided by one ormore co-located or networked devices. In one example, peak detectionmodule 76 and wave detection module 78 may be functional modulesexecuted by processor 72. Similarly in FIG. 2, although the variousmodules 90, 92, 94, 96, 98, and 99 are depicted as separate modules in asingle device, in other examples their functionality may be provided byany one or more devices.

FIG. 2 is a block diagram illustrating an example configuration of wavedetection module 78. In the example of FIG. 2, wave detection module 78comprises a low-pass filter 90, a window module 92, a slope module 94, arectifier module 96, a smoothing module 98, and a threshold detectionmodule 99.

Low pass filter 90 may generally be any low-pass filter designed toreduce or eliminate the high frequency components of electrical signals.Some examples of low-pass filters embodied in hardware includecapacitive low-pass filters and inductive low-pass filters. Otherlow-pass filters may be embodied entirely within software. In someembodiments, low-pass filter 90 is embodied as a combination of hardwareand software. Low-pass filter 90 may be a first, second, or higher orderfilter. In some examples, low-pass filter 90 comprises multiple filtersplaced in a succession in order to create a desired frequency response.In some examples, the low-pass filter 90 is a linear filter with amaximally flat group delay or maximally linear phase response. Aconstant group delay is a characteristic of phase response of an analogor a digital filter, which helps preserve the shape of the signal in thepass-band. In at least one example, the low-pass filter is a Besselfilter with a cut-off frequency of 15 Hz.

Window module 92 may generally window received signals. In someexamples, window module 92 may receive cardiac electrograms, and infurther examples, some of the cardiac electrograms may include a markeror markers indicating one or more points of interest. Some example ofpoints of interest could be the R-wave, the P-wave, or any other wave ofthe cardiac electrogram. In some examples, peak detection module 76 maydetect the locations of R-waves in a cardiac electrogram, according totechniques that are well known in the art, for example using a varyingthreshold. Peak detection module 76 may then place a marker within thecardiac electrogram identifying the location of the R-wave. In otherexamples, other modules or devices may detect and mark waves in thecardiac electrogram. In examples where the signal includes at least onemarker, window module 92 may window the received electrical signalaround the marker.

For example, window module 92 may multiply the received electricalsignal by zero outside of the area around the marker and by one insideof the area around the marker. In this way, window module 92 may modifythe received electrical signal to only contain information in an areaaround the marker. In some examples, window module 92 may isolate theQRS complex. In some examples, window module 92 may window an area ofinterest of equal length around the marker, for instance 150 ms beforethe marker and 150 ms after the marker. In other examples, the area infront of the marker may be longer or shorter than the area behind themarker. In one or more embodiments, the algorithm detects the localmaximums as information for each beat. Specifically, each beat includesseveral local maximums which can represent, for example, the P wave, theQRS wave, and the Twave. Based on the beat information, the channels toupdate the onset of cardiac depolarization are selected. After updatingthe onset of cardiac depolarization, a window, extending a certainamount of time (e.g. 220 ms) is used to detect the activation time. Thewindow can be adjusted by using the onset of cardiac depolarization.Since the window is dependent on the onset of cardiac depolarization,the window also changes with any changes to the onset of cardiacdepolarization.

Slope module 94 may generally determine the slope of a receivedelectrical signal. Some example techniques for determining a slope thatslope module 94 may use are taking the simple difference betweenadjacent points on the received electrical signal, or determining thefirst derivative of the received electrical signal.

Rectifier module 96 may generally rectify a received electrical signal.For example, rectifier module 96 may half-wave rectify the receivedelectrical signal to produce a resulting signal with information onlywhere the original signal was above zero. In another example, rectifiermodule 96 may full-wave rectify the received electrical signal toproduce a resulting signal where all the negative values of the originalsignal are now positive.

Smoothing module 98 may generally smooth a received electrical signal.For example, smoothing module 98 may be configured to increase thevalues of certain points and decrease the values of certain points so asto create a smoother signal. Some example smoothing algorithms includerectangular or un-weighted sliding average smoothing, triangularsmoothing, and Savitzky-Golay smoothing. The smoothing algorithms may beimplemented through one or more filters. In at least one example, thesmoothing filter is 10-order median filter. In another example, thesmoothing filter is a n-order median filter where n is an increasinglinear function of the sampling frequency used to digitize theelectrogram or electrocardiogram signals.

Threshold detection module 99 may generally be configured to determine athreshold and at what points a received electrical signal crosses apre-determined threshold. The threshold may be determined based on amaximum value of the signal received from smoothing module 98. Forexample, as illustrated in FIG. 2, threshold detection module 99 may beconfigured to receive, from peak detection module 76, a maximum value ofthe signal received from smoothing module 98. Threshold detection module99 may be configured to determine a threshold value based on thereceived maximum value. For example, threshold detection module 99 maydetermine the threshold to be ten percent, fifteen percent, twentypercent, or more of the maximum value. Ultimately, threshold detectionmodule 98 may determine the onsets and/or offsets of heartdepolarization and repolarizations waves based on at which points of areceived electrical signal cross a threshold.

Methods 100-300, depicted in FIGS. 3, 7, and 10, ensure that the mostaccurate data is used to update onset data for each beat. Methods100-300 determine onset of depolarization are based on acquiringunipolar cardiac signal from each electrode in response to delivering apace to cardiac tissue. However, determination of onset ofdepolarization can also be determined solely on intrinsic rhythm (i.e.without sending a pacing pulse to test the reaction of the cardiactissue). Onset of data for each beat is determined after implementingmethods 100-300. For example, the first local maximum is located foreach beat and then stored in memory as described relative to FIG. 35.The first derivative data that is smaller than a preselected percentage(e.g. 5% or less, 4% or less, 3% or less, 2% or less, 1% or less etc.)of this first local maximum is considered to be the onset ofdepolarization.

Method 100 is directed to validating ECG data acquired from a pluralityof channels and eliminating channels that are deemed to acquire invaliddata such as channels in which the electrode is detached from thesurface of skin of a patient. Electrodes detached from the skin producesnoise.

The total number of channels used in method 100 is automatically presetor set by the user and stored into memory. For the sake of illustration,in one example, the total number of channels, from which time sampledsignal data is acquired, is set to N1 (e.g. 55). In one or moreembodiments, a preferred range of 30 to 50 channels are employed. Itshould be understood however, that the total number of channels could beany integer in the range of 1-500 channels. In one or more embodiments,the total number of channels can be less than or equal to the followingnumber of total channels: 500 channels, 450 channels, 400 channels, 350channels, 300 channels, 250 channels, 200 channels, 150 channels, 100channels, 90 channels, 80 channels, 70 channels, 60 channels, 50channels, 40 channels, 30 channels, 20 channels, etc. Additionally,method 100 requires counters to be automatically initialized by settingeach counter to preselected values (e.g. I counter is set to 0, etc.).

Referring to block 102 of FIG. 3, signals are acquired and loaded intomemory from electrodes such as body surface electrodes and/or electrodesthat are implanted in a patient's body through an IMD, leadlesspacemaker, and/or medical electrical lead. An exemplary leadlesspacemaker is shown and described in U.S. Pat. No. 8,923,963B2, issuedDec. 30, 2014 and assigned to the assignee of the present invention, thedisclosure of which is incorporated by reference in its entirety herein.

Block 104 verifies whether the total number N₁ of channel data has beenprocessed through method 100. For example, a determination is made as towhether the channel number, presently being processed, is less than thetotal number N₁ of channels. If all of the channel data has beenprocessed, then the present channel number being processed is greater orequal to N₁. Therefore, the NO path can be followed to block 106 inwhich the channel data is completed. In contrast, if the channel numberis less than N₁, the YES path can be followed from block 104 to block108 which allows data sampled from the ECG signal to be indexed. Indexedsamples means that each sample is assigned a consecutive number relativeto the time each sample is located on the signal for that particularchannel. The first sample (Sample 1 or S₁) is located closest to timezero while the last sample (end Sample or S_(end)). For example, 30samples could be indexed relative to the time each sample appears in thesignal. The first sample would be referred to as sample 1 at time 1,sample 2 is at time 2 and so on . . . sample 30 would be at time 30.Exemplary indexed data, sampled from an invalid ECG signal 103 b, isdepicted in FIG. 20. The data is indexed by sample number relative totime provided along the X-axis shown in FIG. 20. As is further shown,the signal includes two different amplitudes A1, A2.

At block 110, a voltage threshold N₂, depicted perpendicular to theY-axis and horizontal to the X axis in FIG. 20, is used to eliminate ordelete indexed samples that may be artifacts at block 112. Artifacts aretypically associated with very large voltages but artifacts can also besmaller signals among the noise level.

The elimination process at block 112 begins with setting N₂. N₂ can beset at 1×10⁴ micro-volts, but the N₂ can be set at any number greaterthan 1×10⁴ micro-volts such as 2×10⁴ micro-volts 3×10⁴ micro-volts,4×10⁴ micro-volts, 5×10⁴ micro-volts . . . to 10×10⁴ micro-volts. Todetermine which indexed samples are deleted, all samples that possess avoltage that is at least equal to N₂, as is shown in FIG. 20, by fourindexed samples S₁, S₂, S₃, and S₄ that cross N₂. After the samples arelocated that cross N₂, the smallest indexed sample is selected. In theexample shown in FIG. 20, the smallest indexed is sample S₁. S₁ crossesN₂ as is indicated by the vertical line that extends from the X-axisthrough the signal. All indexed samples from S₁ to the end of the signalS_(end) at end time point, referred to as t the windowed ECG signal isdeleted. The deleted indexed samples are assumed to include artifacts.An example of an artifact is described with respect to U.S. patentapplication Ser. No. 14/216,100 dated Mar. 17, 2014, and assigned to theassignee of the present invention, the disclosure of which isincorporated by reference in its entirety herein. Artifacts or pacepolarization effects are present on a sensing electrode employed tosense the electrical activity of the heart. While the deleted samplesmay or may not include artifacts, the process of block 112 substantiallyensures artifacts are eliminated. The sample data that remains includesall data that precedes S₁. The remaining sample data continues to block114. With respect to the good ECG signal 103 a, N₂ does not passtherethrough; therefore, the data from the good ECG signal is noteliminated. FIG. 20 corresponds to block 110 by showing sharp spikes,for example, when the patient's body moves. At decision block 114,method 100 checks for another type of artifact in the sensed signal suchas small signals among the noise level. Additionally, at least onecardiac cycle has been sensed by setting the number N₃ of samples withina pre-specified time period to an adequately high number of samples(e.g. 200 ms, 175 ms, 150 ms, 125 ms, 100 ms etc.). The samples aresearched backwards from the last to the first sample. For example, adetermination is made as to whether VALUE (I) minus (−) VALUE (I+N₃(e.g. 200 ms)) is less than N₄ (e.g. 10) where N₄ checks how the signalchanges in magnitude within the 200 samples. N4 can be some otherpre-selected number based upon patient specific data. For example, N4can be set to 30, 20, 15, 10, etc. but is generally less than 30. Therange of QRS duration which can be as short as 100 ms but could also beas long as 250 ms. N₃ can be set to an integer such as such as 100-250samples. The sample numbers, provided herein, apply to a sampling rateof 1000 Hz. For different sampling rates, N₃ would be different.

If the value (I)-value (I+200) is less than N4 (e.g. 10), then the YESpath is followed to block 116 in which a I counter is decreased by 1which allows the samples to be evaluated from the last sample that wasrecorded or stored into memory. For example, the counter I isdecremented by the equation I=I−1 which allows the samples to beprocessed from the last sample to the first sample stored into memory.If the VALUE(I)−VALUE (I+N₃) is not less than N₄ (e.g. 10), then the NOpath can be followed from block 114 to block 118.

At block 118, samples from “I”, referred to relative to block 116, aredeleted to the end. While the samples that remain in block 116 aredifferent from the samples at block 112, the same or similar concept isapplied to deleting samples as that which was described relative to FIG.20, which is incorporated herein. The entire noise signal shown in FIG.5 is eliminated at block 118 because the magnitude of the change of thesignal is very small. The noise signal is a linear step function orconsidered a flat line. The graph in FIG. 5 ranges from −5.4×10⁻¹⁰microvolts to −5.1×10⁻¹⁰ microvolts while the X-axis ranges from 0 to 3milliseconds.

At decision block 120, a determination is made as to whether thesamples, that remain after deleting samples at block 118, are greaterthan a preselected number such as N₃. If less than or equal to N₃remain, then the YES path continues to block 134 which causes the dataacquired from that channel to be declared invalid. Invalid data from achannel is not a good channel to update onset of QRS wave data. Invalidchannel data can be designated by “0” which is distinguished from validdata designated as “1”. The designation of channel data as valid orinvalid is stored in a data register that is associated with eachchannel.

If greater than a preselected number N₃ of samples remain, the YES pathcan be followed to block 122. At block 122, the first derivative isdetermined. The first derivative along with the amplitude of the signaldetermine whether the signal is sufficiently strong. The firstderivative can be determined by calculating the change or delta of theY-axis divided by the change or delta of the X-axis as to the signaldata. At block 124, the second derivative is determined. The secondderivative can be calculated by determining the change or delta of twopoints along the Y-axis divided by the delta of the two points on theX-axis of the Y derivative.

At block 126, a determination is made as to whether the secondderivative data is less than N₅. N₅ is data dependent and is a verysmall value. For example, N₅ can be set at 1×10⁻⁶ microvolts. Sampledata, having second derivative data greater than N₅, are kept while theremaining samples are deleted. Specifically, any second derivative dataless than or equal to N₅ is eliminated from further processing of data.Block 126 eliminates flat-line signals such as that which is shown by anexemplary second derivative of an ECG signal of FIG. 6. If the samplevoltage is less than or equal to N₅, the process continues to block 128,which relates to determining whether sampled data that has beenprocessed is greater than X₁% of the total number of samples. X₁ can beset at any substantially high percentage of samples that have beenprocessed out of the total number of remaining samples. Exemplary X₁%can include 80%, 85%, 90% or 95%.

If the sample data being processed indicates greater than X₁% of thetotal samples have been processed through method 200, then the YES pathcontinues to block 132 in which the channel data is deemed invalid andthe process continues on to block 104. In contrast, if the sample is notgreater than X₁%, then the channel data is considered valid. A goodchannel can be designated by “1” while a bad channel can be designatedwith a “0” which is stored in the data register and the control logic isreturned to block 102.

Method 200, depicted in FIG. 7, determines the channel that is able toacquire the strongest signal or a signal with high fidelity or crispnesssuch as a a good amplitude, strong slew rate (i.e. slope of a waveform).More specifically, method 200 checks a signal, beat by beat, from aspecific channel to determine whether the signal is adequately strongenough to be used to update onset data. Channels that can be used toupdate onset data are distinguished from channels that cannot be used toupdate onset data.

Generally, method 200 assigns a “leadchannel” for each a channelconnected to an electrode. Each beat sensed via a channel is assigned a“beat sign” to distinguish beats within a set of beats sensed throughthe channel. Starting from the first channel, a set of beats areacquired within a pre-specified time frame. Beat information is capturedby local maximums. After separating the one-channel signal by beats,local maximums are checked for each beat. Local maximum is a maximum(e.g. amplitude) associated with a beat within a time window.

At block 202, N₆ valid channel signals were determined from method 100and are stored into memory. N₆, determined through method 100, can beset to an integer such as 10, 20, 30, 40, 50, 56, 60, 70 etc.

At block 204, a determination is made as to whether a counter, referredto as I₂, is less than N₆+1. I₂ is the number of channels that has beenupdated in FIG. 7.

If I₂ is not less than N₆+1, the NO path can be followed from block 204to block 206, which indicates that data from all of the valid channelshave been processed; therefore, the process of checking all channel datais completed. If I₂ is less than N₆+1, then the YES path can be followedfrom block 204 to block 208, which requires data to be accessed frommemory for that particular channel in order to determine the strength ofthe slew rate. Data accessed from memory for block 208 was generatedfrom instructions executed in FIG. 10. Block 208 accesses the square ofthe first derivative data, stored in memory from the execution ofinstructions described relative from FIG. 10. Exemplary data accessedfrom memory is the square of the first derivative. The square of thefirst derivative could have been previously calculated and stored intomemory for the signal or the data is calculated after the processoraccesses the signal data from memory. Additionally, each local maximumis determined and stored for each beat.

At block 210, a determination is made as to whether a mean of the localmaximums beat to beat is greater than N₈ such as 200 mV. Typically, N₈can range from about 3.5 mV to about 200 mV. Mean is the average of allof the local maximums within a window. If the mean of the local maximumfor each beat is not greater than N₈, the NO path can be followed fromblock 210 to block 214 which indicates that the channel data is validbased on method 100, but the signal acquired from the channel is notstrong enough to be used for updating onset data. If the mean of themaximum of each beat is greater than N₈, then the YES path can befollowed from block 210 to block 212, which requires a determination tobe made as to whether the number of sampled beats from a channel isgreater than N₈ beats (e.g. 50 beats) within a predetermined time periodsuch as 30 seconds. N₈ is set to a substantially high number such as 50beats per 30 seconds compared to a normal heart beat of 30 beats per 30seconds. A substantially high number of beats within 30 seconds causesthe YES path to be followed to block 214, which indicates thatparticular channel data is considered valid but is not strong enough tobe used for updating onset data If the number of beats per 30 seconds isnot greater than N₈ beats, then the NO path can be followed from block214 to block 216, which sets a beat counter, referred to as BEAT, equalto 1.

Block 218, requires the processor to store and/or acquire from memory,beat to beat data that is compared to M. For example, local maximuminformation corresponding to each beat for a channel signal is storedinto memory. Thereafter, block 218 determines whether all of the beatand local maximum data has been processed and stored into memory.Exemplary local maximum data within one beat is shown in the window ofFIG. 8 while FIG. 9 displays two different local maximums correspondingwith two different beats within a time window. To determine whether allbeat and local maximum information has been processed and stored intomemory, block 218 requires a determination be made as to whether BEAT<Mwhere BEAT is the number associated with the beat data that is beingprocessed or has been last processed while M is the last beat number orthe total number of beats.

According to block 218, if BEAT<M, the YES path indicates that all ofthe beat and local maximum data has been processed and stored intomemory. The YES path from block 218 can be followed to decision block220. At block 220, a determination is made as to whether the beat tobeat data stored in memory indicates greater than a preselectedpercentage X₂% (e.g. 75%, 80%, 85%, 90%, 95% etc.) of beat data isconsidered valid. If greater than, for example, 75% of beat data for aparticular channel is considered valid, then that channel is deemedvalid at block 222 and the channel can be used to update the onset on aone time only basis or on a continuous basis. In contrast, at block 220,if the beat to beat data stored in memory indicates equal to or lessthan a preselected percentage of (e.g. 75%, 80%, 85%, 90%, 95% etc.)beat data is considered valid, then the data acquired from thatparticular channel is considered valid but not sufficiently strong atblock 214 and will not be used to update the onset data.

Returning to block 218, if BEAT is not less than M (i.e. last beatnumber or the total number of beats) the NO path to block 224 indicatesthat the beat data is still being processed and stored into memory.

Each beat is checked to determine how many local maximum in each beat islarger than 10% of the mean at block 210. After a determination is madeas to whether any local maximums exist over 10% of the mean of the localmaximums for each beat are present, the number of local maximums, ifany, over 10% are stored into memory (e.g. memory of the programmer).

After acquiring information for each beat, blocks 225-230 determine howmany local maximums are within a designated region. For example, atblock 225, if there is one local maximum within a window, then the YESpath can be followed to block 232. At block 232, after deleting thepresent maximum value within the window, any remaining local maximumsare located and counted that are within the window.

At block 234, a determination is made as to whether greater than twolocal maximums are within X₃% (e.g. 90% etc.) of the maximum amplitudeof the remaining local maximums. Essentially, block 234 determines whichlocal maximum is the largest within the window and then also determineswhether greater than two local maximums are within X₅% (e.g. 90% etc.)of the maximum amplitude of the signal. If there are greater than twolocal maximums, the beat counter is set equal to zero at block 236. Thebeat counter is incremented by 1 through the equation BEAT=BEAT+1 atblock 238. Thereafter, the process continues to block 218.

Returning to block 225, the NO path indicates that the beat data hasbeen processed and can now be classified with respect to detection ofbeats per window at blocks 226, 228, and 230. Decision block 226determines whether two local maximums are present in a window. If so,then the YES path can be followed from block 226 continues to decisionblock 242 in which another determination is made as to whether a minimumbetween the present two local maximums is less than a preselectedpercentage X₄% (e.g. 5%) of the local maximum.

The NO path can be followed from block 242 to block 236 in which BEATcounter is set equal to zero. In contrast, the YES path can be followedfrom block 242 to block 240 in which the BEAT is set equal to one.Thereafter, the BEAT counter is incremented at block 238 and then theprocess continues at block 218.

Returning to block 226, the NO path continues to block 228 in which adetermination is made as to whether three local maximums are located andcounted within a window. If so, then the YES path continues to decisionblock 244. At block 244, the value of the smallest local maximum withina window is determined. It is then determined whether more localmaximums within a window are within a preselected percentage of thevalue of the smallest local maximum. Through the comparison, adetermination can be made as to whether the local maximum is within thepreselected percentage of the smallest local maximum within a window.The YES path can be followed from block 244 to block 236 in which theBEAT counter is set equal to zero. The NO path can be followed fromblock 244 to block 240 in which the BEAT counter is set equal to one.

The NO path from block 228 continues to block 230 in which adetermination is made as whether four local maximums within a windowthen the process continues to block 236 in which the BEAT counter isequal zero. In contrast, the NO path can be followed from block 244continues to block 240 which causes BEAT=1.

Data, stored into memory as a result of execution of computerinstructions generally depicted in FIG. 7, is used to initializeparameters associated with FIG. 10. However, skilled artisans willappreciate that step 208 of FIG. 7 accesses data from memory that isacquired from execution of instructions generally embodied in FIG. 10.In one or more embodiments, step 208 serves as a call function toexecute a subroutine (e.g. first derivative etc.) and store the dataresulting from the subroutine into memory.

Method 300, depicted in FIG. 10, ensures that only the most accuratesignal data is used to calculate the onset depolarization data. Inparticular, method 300 determines the beat information. The beatinformation is acquired and stored into memory through FIG. 10 beforethe onset is updated for each beat. For example, method 300 determines amaximum for each beat that is acquired from a signal on a channel toensure only the most accurate onset depolarization data is obtained.Method 300 further eliminates unnecessary artifacts that may be found inthe signal while also ensuring that beats are not missed. Essentially, adetermination is made as to how separated in time the local maximums areto each other, as is shown in FIG. 23. For example, assume one timeindex sample is 100 while another shown at time index sample is 1600. Aset of local maximum is shown at time index sample 100 while only onelocal maximum is shown at time index sample 1600. The difference betweenthe two time index samples is 1500, which indicates how separated intime the local maximums are to each other.

In order to eliminate unnecessary artifacts and/or ensure beats are notmissed, a ratio value R is adjusted in method 300. For example, if thedifference of the time sample indexes of the neighboring local maximumis larger than N₁₀ (e.g. sample index 1500) then beats were missed orskipped. In order not to skip beats, the ratio value R is decreased toobtain a new R so that beats are not skipped. Additionally oralternatively, if the difference of the indexes of the neighboring localmaximum is smaller than N₁₁ (e.g. sample index 400). unnecessaryartifacts are found between two beats. In order to eliminate unnecessaryartifacts, the ratio value is increased to a new R at block 326.

Method 300 begins at block 302 in which a series of calculations areperformed. For example, the first derivative can be calculated, aspreviously described or through any other suitable method. The square ofthe first derivative is then determined.

Block 304 ensures every signal datum are computed. For example, adetermination is made as to whether I<N₉, in which N₉ was previouslydefined. The NO path can be followed from block 304 to block 312 inwhich the second derivative is calculated as previously described orthrough any other suitable method. The YES path from block 304 continuesto block 306 in which another determination is made as to whether thesquare of the first derivative value is greater than R*M₂ where R is aratio value (e.g. 0.10) can be selected as any other number based ondata statistics. M₂, shown in FIG. 11, is considered the maximumamplitude of the entire ECG signal shown in a time window that extendsup to 3×10⁴ milliseconds.

For signals that are similar to the signal depicted in FIG. 12, onelocal maximum is much larger than the rest. In this situation,information could be missed for numerous beats. Therefore, the algorithmchecks to see if the maximum (i.e. M3) of those local maximums are muchlarger than the mean. For signals like FIG. 12, the maximum M3 willdefinitely be much larger than the mean. Therefore, the algorithmdeletes the maximum M3 and repeats method 300 to get the beatinformation.

The YES path from block 306 continues to block 310 in which the counterI is incremented by 1 and the process continues to block 304. The NOpath from block 306 continues to block 308 in which the differentialequation is set equal to zero. Setting the differential equation equalto zero locates the critical points such as local maximums and minimums,referred to as local extrema, on a function's graph. Local extrema occurat critical points of the function such as where the derivative is zeroor undefined.

Returning to block 312, after the second derivative has been calculated,the local maximums within a window can be determined at block 316. Thesecond derivative test can be used to find critical points such as localmaximums or minimums. The local maximums are found by using the sign ofthe second derivative. The sign of the second derivative test is provideas follows:

If df/dx (p)=0 and d2f/dx2 (p)<0, and d2f/dx2(p+1)>0 then f(x) has alocal minimum at x=p.

If df/dx (p)=0 and df/dx (p)>0, and df/dx(p+1)<0 then f(x) has a localmaximum at x=p.

Rectified signals, shown in the FIGS. 8-9, depict critical points (e.g.local maximums) in a single direction, to ease the physicians reading ofthe signal.

At block 316, a determination is made as to whether local maximums existwithin a window. The NO path from block 316 continues to block 318 inwhich the channel is considered a bad channel or an unacceptable channelfrom which to update onset data. A channel designated as a bad channelis stored into memory and will not be used to update the onset. The YESpath from block 316 continues to block 320. At block 320, the secondderivative is calculated as previously described and stored into memory.At block 322, the index of the first local maximum of a preselectednumber of samples is stored into memory. Exemplary first local maximum317 d is shown in FIG. 35. FIG. 35 depicts a group of local maximumsassociated with an ECG signal acquired from an unipolar electrode.Starting from local maximum 317 a, a determination is made as to thedistance (D1) to the next local maximum 317 b. If the distance (D1) istoo small (i.e. smaller than a threshold) then local maximums 317 a,bare counted as one or less than one beat. The minimum time thresholdbetween each beat can depends on each patient. An exemplary thresholdcould be based upon the threshold that is reliant on the samplingfrequency (e.g. 200 samples is 1 heart beat etc.) which is dependentupon the machine employed for performing the present disclosure.Exemplary sampling frequencies for the machines implementing methods100-300 may range from 100 to 1000 Hertz. The threshold can becustomized for each patient and inputted by the user. Additionally,local maximum data 317 b is not being recorded. A determination is thenmade as to the distance (D2) between local maximum 317 a to the localmaximum 317 c. If the distance (D2) is still too small (i.e. smallerthan a threshold) then local maximums 317 a,b,c are counted as one orless than one beat and local maximum data 317 c is not recorded as afirst local maximum. Yet another determination is made as to thedistance (D3) from local maximum 317 a to the local maximum 317 d. Ifthe distance (D3) is greater or equal to the threshold indicative of anew heart beat, then local maximum 317 d is determined to be the firstlocal maximum. The first local maximum for the new beat is stored intomemory.

At block 324, a determination is made as to whether a difference from anindex of one local maximum to another is larger than N₁₀ or smaller thanN11.

The NO path from block 324 continues to block 328 whereas the YES pathcontinues to block 326.

At block 326, the ratio is changed. The ratio is changed if thedifference of the indexes of the neighboring local maximum is largerthan N10, as shown in FIG. 11. A difference of the indexes of theneighboring local maximum larger than N₁₀ means some beats may have beenmissed, as shown in FIG. 12 in which the local maximums are too farapart. Therefore, the ratio value must be decreased. For example, theratio can be set to 7.5% or R=0.075. In contrast, if the difference ofthe indexes of the neighboring local maximum is smaller than N₁₁, thenartifacts may be located between two beats. Therefore, the ratio valuemust be increased to address skipped beats as shown in FIG. 12. Forexample, the ratio can be 12.5% or R=0.125.

At block 328, the local maximum in each beat is located using the newlymodified ratio. The local maximums are found by determining the firstderivative of the ECG signal, as previously explained. At block 330, themean of local maximums in a beat are determined. The mean is obtained byadding local maximum values together and dividing by the number of localmaximums within the time window.

At block 332, local maximum(s) larger than twice the mean is deleted oreliminated since the much larger local maximums are likely to be anartifact. Referring to FIG. 12, the local maximum designated as M3 isclearly twice as large as the mean of local maximums. At block 334, themean of the remaining local maximums is calculated.

At block 336, a determination is made as to whether a first loop hadoccurred. The NO path from block 336 continues to block 338 and theprocess is stopped. The YES path from block 336 returns to block 302.After the computer instructions for FIG. 10 are completed. Afterdetermining which lead is sufficiently adequate to update onset data,onset of data can be determined for each beat.

For each beat, the process starts from the first local maximum which isupdated by the methods described herein. The data is searched backwardsuntil the square of first derivative is smaller than a pre-specifiednumber (e.g. 10% or less 8% or less, 6% or less, 5% or less, 4% or less,or 2% or less) of the first local maximum associated with a particularbeat, such as the first local maximum 317 d depicted in FIG. 35. Forexample, for each beat, start from the first local maximum which isupdated in FIG. 10 and search backwards until the square of firstderivative is smaller than a preselected percentage (e.g. 5% etc.) ofthis local maximum (i.e. first local maximum). The onset is smaller than5% of this local maximum M, as shown in FIG. 24. Local maximum M isgenerated from instructions executed in FIG. 10. FIG. 24 demonstratesthe last step which is updating the onset. FIGS. 13-14 provide exemplarydata as to FIG. 24. FIG. 13 is an ECG signal in which the onset isdetected at the point x=7569. FIG. 14 is the square of the firstderivative of the ECG signal. It uses the algorithm shown in FIG. 24,searching backwards from the first local maximum until the square offirst derivative is smaller than a preselected percentage (e.g. 5% etc.)of this local maximum (i.e. first local maximum) which is x=7569. FIGS.13 and 14 demonstrate the algorithm, graphically represented in FIG. 24,is correct.

Once the square of first derivative is smaller than 5% of the firstlocal maximum, a determination is made that the onset of depolarizationhas been found and further searching for the onset is terminated. Theonset of depolarization is set equal to the square of the firstderivative that is less than the pre-selected percentage of the firstlocal maximum. Once the onset of depolarization of the ECG has beenfound, the onset of depolarization is updated (e.g. stored in the memoryof the programmer) in the system, which will increase the accuracy fordetermining the activation time calculation and distribution display. Inone or more embodiments, the onset of cardiac depolarization isdetermined solely using implantable electrodes. The IMD is then updatedwith a more accurate onset of cardiac depolarization. Therefore,accurate onset data helps a physician to make the best decisions inchoosing the proper treatment for the patients.

Exemplary instructions for one or more embodiments of the entirealgorithm are presented below.

-   1. Identify valid channels and eliminate invalid channels as shown    and described relative to FIG. 3. Keep the valid channels. Assign a    name such as “channelsign” to each channel.    -   a. Start from the first channel (box 104).    -   b. Start from the last sample for a particular channel, search        for the indexes until the value of the sample is smaller than        threshold level such as 1×10⁴ microvolts. Thereafter, eliminate        samples from the smallest indexed sample to the end (box 112).    -   c. Continue searching backwards (i.e. last sample to first        sample). If the value change is less than 10 within 200 samples        (i.e. 10 checks how the signal changes in magnitude within the        200 samples), continue until larger than 10, and delete those        samples until the end (box 112, 114).    -   d. Then determine if more than 200 samples are still left (box        114). If not, set channelsign to 0 and stop.    -   e. If larger than 200 samples, calculate the second derivative        of the signal (boxes 122, 124). Search from the last sample        until the second derivative is larger than 10⁻⁶ microvolts (box        126) and record the number of samples. If the number is larger        than 90% of the number of all samples, set channelsign to 0.        Otherwise, set channelsign to 1.-   2. The channel number is increased by one. Determine whether the    channel number is larger than the total number of channels (i.e. 56)    being processed (box 104). If yes, stop (box 106). Otherwise, go to    step b.-   3. Referring to FIG. 7, select proper channels (i.e. channels that    remain after execution of instructions from FIG. 3) that can be used    to update the onset data. For the remaining channels, find those    channels that are proper to update the onset. Assign a “leadsign” to    each channel. For each channel, assign a “beatsign” to each beat.    -   a. Start from the first channel and find how many beats are in        this data set.    -   b. If the mean (box 210) of the maximums for each beat is less        than 200, then the channel is not used to update onset. Go to        step f.    -   c. If there is more than 50 beats found (box 212), then the        channel is not used to update onset. Go to step f.    -   d. Check through each beat. Find how many local maximum in each        beat are larger than 10% of the mean (210).    -   If the number is 1 (box 225), delete this local maximum and find        the local maximum after the elimination of this local maximum.        If more than or equal to three local maximums are larger than        the 90% of the maximum of the remaining data in this beat,        assign beatsign as 0; otherwise, beatsign will be 1.    -   If the number is 2 (box 226), check if the minimum between these        two local maximums is less than pre-selected amount (e.g. 5%) of        the maximum. If yes, assign beatsign as 1, otherwise beatsign=0.    -   If the number is larger than or equal to 4 (box 230), assign        beatsign as 0.    -   If the number is 3 (box 228), find the value of the smallest        local maximum and search to see if there are a fourth or even        more local maximums those values are within 80% of the smallest        local maximum value. If yes, beatsign is set to 0. Otherwise,        beatsign is set to 1.    -   e. If more than 75% of the beatsign are 1, then the lead can be        used and assign leadsign as 1 for this lead (box 220).        Otherwise, assign leadsign as 0.    -   f. Go to the next valid channel. Check if the channel being        processed is the last one of the total number of channels being        processed. If yes, stop. Otherwise go to step b.-   4. FIG. 10 updates and stores the beat information by finding how    many beats are in this data set. The result from FIG. 10 is accessed    by FIG. 7 operations. The first maximum is located which is larger    than 10% of the mean of maximums for each beat.    -   a. Calculate the square of the first derivative of the signal        (box 302).    -   b. Find samples that are larger than 10% of the maximum of        square of first derivative (box 306). Those smaller ones are set        to zero and assigned to another matrix.    -   c. Find the second derivative of these samples (box 312). Use        the first derivative to find local maximums (box 314). If no        local maximum exists (box 318), give a sign to the function        “isgoodlead” to set leadsign for this channel as 0, and stop.    -   d. Set the indexes of those local maximum to the same values if        they are within 500 samples. After “unique” command, the rest        are the indexes of the first local maximum in each beat.    -   e. If the difference of these indexes are larger or smaller than        1500 or 400, change the ratio to 7.5% or 12.5% and re-process        (box 324).    -   f. After that, find the maximum in each beat. The maximum in        each beat is not the value of the first local maximum. Calculate        mean of these maximums. Delete maximums which are larger than        twice of the mean (box 332). Re-calculate the mean (box 334).        Also, use the recalculated mean as the criterion, instead of the        maximum of the first derivative, and re-do the procedure from        step b (box 336).-   5. Update onset data.

For each beat, start from the first local maximum, which is updated instep 3, and search backwards until the square of first derivative datais smaller than 5% of this first local maximum. FIG. 35 and theaccompanying text describe the manner in which the first local maximumis located for each beat and then stored in memory. The first derivativedata that is smaller than a user inputted percentage (preselectedpercentage e.g. 5% or less, 4% or less, 3% or less, 2% or less, 1% orless etc.) of this first local maximum for a beat is considered to bethe onset of depolarization. Onset data is updated for each beat. Afterthe onset data has been updated, the signal can undergo further signalprocessing. For example, method 1200 depicted in FIG. 25 and/or method1300 depicted in FIG. 29 can be used to further improve upon the onsetdata obtained from methods 100-300. Method 1200 determines whether asignal, acquired from a channel of a multichannel mapping system, isvalid or is invalid due to artifacts. In particular, method 1200determines whether a beat, within a window that extends up to 200 ms, isa valid QRS wave.

Method 1200 begins at block 1202 in which the onset of thedepolarization is updated, as described herein with respect to methods100-300. At block 1204, a determination is made as to whether eachchannel connected to an electrode has had its signal processed. Thetotal number of channels used in method 1200 is automatically preset orset by the user and stored into memory. For the sake of illustration, inone example, the total number of channels, from which time sampledsignal data is acquired, is set to N1 (e.g. 55). In one or moreembodiments, a preferred range of 30 to 50 channels are employed.Additionally, method 1200 requires a counter to be automaticallyinitialized by setting the counter to a preselected value (e.g. set to0, etc.) that allows each channel to be counted in order to ensure data,from each channel, is processed. The NO path from 1204 continues toblock 1220 which indicates all channels have finished being processedthrough method 1200 and are deemed to acquire either valid or invalidsignals. The YES path from block 1204 indicates that a channel stillmust undergo method 1200 operations and therefore continues to block1206.

At block 1206, a first derivative is calculated from a signal acquiredfrom an electrode (e.g. surface electrode etc.) and stored into memory.FIG. 26 depicts an exemplary first derivative of a signal. The maximumof the first derivative 1224 depends on the detected onset of theacquired signal. The maximum of the first derivative 1224 exhibits apositive slope along the dashed line since the curve rises. The minimumof the first derivative 1222 exhibits a negative slope at the dashedline. The ending of the minimum of the first derivative 1222 depends onthe size of the time window. Baseline 1226 is displayed merely toprovide context to the first derivative of the signal within the window.

At block 1208, a determination is made as to whether the signs aredifferent for the waveform. If the signs are the same, the NO pathcontinues to block 1216 where the signal is declared invalid. If thesigns are different, the YES path from block 1208 continues to block1210. Different signs are shown by the exemplary waveform depicted inFIG. 26. The minimum of the first derivative shown in FIG. 26 possessesa negative sign. The maximum of the first derivative 1224 shown in FIG.26 possesses a positive sign. FIGS. 28A-D provide several otherexemplary waveforms that exhibit a positive and negative slopes. Forexample, FIG. 28A is a typical R waveform, FIG. 28B is a biphasic QRSwaveform, FIG. 28C is a R-s waveform, and FIG. 28D depicts a QSwaveform. A valid R wave exhibits a minimum of the first derivative inwhich the curve exhibits a downward or negative slope and a maximumderivative that exhibits a rising or positive slope, and a ratio that isclose to each other. In contrast, the waveform in FIG. 27 is an artifactsignal in which the maximum (positive) and minimum (negative) slopes areindicated by the dashed black and solid black lines respectively. Themaximum positive slope has value of 0.00002 microvolts/ms and theminimum negative slope has value of −17.6 microvolts/ms.

At block 1210, a ratio is calculated of the absolute value taken of thelarger one of derivatives in the numerator over the smaller one of thederivatives in the denominator. Accordingly, the magnitude of themaximum and minimum of the derivative determine the numerator anddenominator for the ratio calculation. An exemplary ratio calculationcan be shown with respect to FIG. 27. Taking the ratio of themagnitudes, the ratio value is 17.6/0.00002=8,80,000 which is a largenumber and indicates that the signal is not a physiologically validsignal, rather, the signal is an artifact. If the signs are the same foreach slope, then artifacts have been confirmed to have been detected andthe signal acquired from the channel is deemed invalid at block 1216.

At block 1212, a determination is made as to whether the ratiocalculated at block 1210 is greater than a preselected number C (e.g.5). C can range from 2 to 12. If the ratio is not greater than thepreselected number C from block 1208, then the NO path from block 1212continues to block 1214 in which the signal acquired from a channel isconsidered valid. If the ratio is greater than the preselected numberfrom block 1210, then the NO path from block 1212 to block 1214indicates the signal is considered valid.

Signals from blocks 1214 and 1216 continue to block 1218. At block 1218,the channel number counter is increased by 1 then checked at block 1204to ensure all of the channels are processed. Blocks 1202-1212 arerepeatedly performed until each channel of the total channels N1 arecompleted. Skilled artisans understand that method 100 and/or method1200 can be applied to any signal to eliminate artifacts. For example,methods 100 and 1200 can also be used with any physiological signal(e.g. cardiac signal, neural signal etc.) acquired from the body of thepatient using surface electrodes and/or implanted electrodes.

In addition to eliminating artifacts, other embodiments of the presentdisclosure can be implemented to determine whether an ambiguous signalis being detected from an electrode during any activation mapping usedin a variety of electrophysiologic procedures. Activation mapping caninvolve mapping directly from the surface of the heart, from within thecavity of the heart or from the body belt developed for cardiacresynchronization. Other examples may include multi-electrode arrays(e.g. constellation baskets) in combination with a catheter that canthen be deployed in the intracardiac space for simultaneous orsequential mapping of electrical activity of the heart surface usingsurface electrodes. FIG. 29 depicts method 1300 for identifyingambiguous cardiac signals during electrophysiologic mapping. Ambiguoussignals may occur during atrial fibrillation (AF) mapping and/or anelectrode being placed near or in a poor substrate (e.g. scar tissue).Ambiguous cardiac unipolar signals can exhibit a morphology withmultiple negative slopes of comparable magnitudes within a singlewindow, thereby making it difficult to identify the activation-timeuniquely acquired from that electrode. Method 1300 detects suchambiguous signals, and automatically “edits” the activation timescorresponding to those electrodes based on activation times fromneighboring electrodes with non-ambiguous signals. Method 1300essentially uses activation times from neighboring electrodes todetermine the correct activation time in response to determiningambiguous signals are being acquired from an electrode. Acquiringactivation times using surface electrodes is described in U.S. patentapplication Ser. No. 14/227,919 to Ghosh et al., filed on Mar. 27, 2014and 61/817,240 filed on Apr. 30, 2013 and is entitled, SYSTEMS, METHODS,AND INTERFACES FOR IDENTIFYING OPTIMAL ELECTRICAL VECTORS” and isincorporated herein by reference in its entirety.

Skilled artisans will appreciate that method 1300 can be applied to anybiosensed signals. For example, method 1300 can be applied to electricalsignals acquired from an electrode apparatus described herein and/orelectrodes implanted in the patient's body and/or subcutaneouselectrodes. Method 1300 also can be applied to a constellation orbasket. Method 1300 can also be applied to a balloon on a delivery toolor catheter. Additionally, method 1300 can be implemented using a movingprobe.

The data, generated by implementing blocks 1302-1310, are previouslydescribed herein and incorporated by reference in their entirety. Thedata is automatically stored in memory immediately after beinggenerated. Computer instructions e.g. firmware can be used toautomatically store data generated from any one of the blocks in any ofthe flow diagrams presented herein.

Method 1300 begins at block 1302 in which the onset data is determinedand stored into memory. Onset data can be obtained from FIGS. 3, 7 and10 or acquired from the sensed signal. At block 1304, the firstderivative is calculated of a signal, as previously described, andstored into memory. An exemplary ECG signal is shown in FIG. 30 with itscorresponding first derivative curve shown in FIG. 31. The firstderivative is used to identify the timing of a steepest negative slopeof the signal for determining the activation time corresponding to aparticular electrode. The signal can be acquired from one or moreelectrodes disposed on the surface of the heart, from within the cavityof the heart, or from the body surface using surface electrodes. FIGS.32 and 33 show exemplary signals with dashed lines intersecting at thesteepest point of each curve.

At block 1306, the local maximum and local minimums are located within awindow using know techniques. One exemplary technique involves comparingone point to another point along the curve until all the points alongthe curve have been processed. The technique may include a sortingoperation and/or swapping operation to determine minimum and maximumderivative data points. For example, two of the largest local minimum ina window should have at least one local maximum therebetween. Derivativedata for local maximums and local minimums is helpful to define regionssince first derivative maximums and minimum should be zero.

At block 1308, the value of minimum of the first derivative and itscorresponding time index in each region is recorded. The time indexrelates to the indexed sample as described relative to FIG. 20. Minimumderivative and its corresponding time index in each region is shown anddescribed in method 100 and is incorporated by reference herein.

At block 1308, two minimum derivatives are located within a windowextending a pre-specified time period (e.g. 200 ms). The two minimumderivatives having the largest magnitudes (i.e. absolute values) among aset of minimum derivatives are located within the window. Sorting and/orswapping operations may be used to determine two minimum derivatives.

At block 1312, a ratio is calculated. The ratio uses the followingformula:

ratio=abs(larger one of the minimum derivatives)/abs(smaller one of theminimum derivatives) where “abs” represents the absolute value.

Additionally, the timing difference (“dis”) between the absolute (“abs”)value of the difference between a first and second index are calculatedusing the following equation where index1 and index 2 are the timeindices corresponding to the two minimum derivatives:

dis=abs(index1−index2)

where index1 relates to the derivative data with the larger magnitude(i.e. “larger one” block 1210 FIG. 25) and index2 relates to thederivative data with the smaller magnitude (i.e. “smaller one” block1210 FIG. 25).

At decision block 1314, a determination is made as to whether thedistance between the two indices is less than a pre-selected number suchas 10 ms. The pre-selected number is typically in a range of about 5 toabout 15 ms. The YES path from block 1314 continues to block 1316 whichindicates the signal is valid. The process is completed or finished atblock 1322. The NO path from block 1314 continues to decision block1318.

FIG. 34 depicts an ambiguous signal. The ambiguous signal includes twominimum slopes (i.e. steepest slopes) that are nearly equal and areseparated by a distance (dis) of time that is less than the pre-selectednumber. If two separate slopes are about equal but are widely separatedin time, then the signal acquired from a channel may be ambiguous fromthe standpoint of activation time detection. An ambiguous signal canstill be a valid physiologic signal and may not be an artifact. Butthere is an element of ambiguity in determination of derivative-basedactivation time from such a signal. Decision block 1318 confirms whethera signal is ambiguous. For example, at block 1318, a determination ismade as to whether the ratio is greater than a pre-selected number (e.g.where the pre-selected number can be any number from 1 to 5). The NOpath from block 1318 continues to decision block 1320 which indicatesthe signal is ambiguous.

The YES path from block 1318 continues to block 1316 which indicates thesignal is non-ambiguous (from the standpoint of derivative-basedactivation time determination). After determining whether a signalacquired from a channel is ambiguous or non-ambiguous, the process isfinished at block 1322 for that particular channel. Method 1300 isrepeated for each channel connected to an electrode until each signalchannel has been processed.

The present disclosure can identify the timing of steepest negativeslope of an unipolar ECG/cardiac signal for determining the activationtime corresponding to a particular electrode. If the cardiac unipolarsignal has a morphology with multiple negative slopes of comparablemagnitudes, the present disclosure is able to identify theactivation-time uniquely from that electrode, and reviews activationtimes from neighboring electrodes to determine the correct activationtime.

FIGS. 15-19 and 21 are conceptual diagrams illustrating an examplesystem 910 that is useful for obtaining an accurate onset and/or offsetpoints of heart depolarization and repolarization waves of patient 914according to the techniques described herein. As with the previouslydescribed system, in one example, system 910 may detect the onset and/oroffset points of heart depolarization and repolarization waves in orderto select a preferred location for implanting an intracardiac lead. Inother examples, system 910 may detect the onset and/or offset points ofheart depolarization and repolarization waves in order to select otherparameters based on the electromechanical delay. For example, the systemmay select a particular pacing electrode configuration or pacingintervals for cardiac resynchronization therapy. In another example,with multipolar leads offering choices of more than one pacing electrode(cathode) in the ventricle, the system/device may automatically pacefrom each of the pacing electrodes at maximum pacing voltage and at anominal atrio-ventricular delay (˜100 ms) and measure onsets and offsetsof the resulting depolarization waveforms on a far-field electrogram oron a leadless ECG or on a surface ECG lead, and choose the pacingelectrode which produces the minimum difference between the offset ofthe local electrogram and the corresponding far-field onset, fordelivery of cardiac resynchronization therapy. Alternatively, the pacingelectrode which produces the narrowest far-field electrogram or surfaceECG signal calculated as the difference between the offset and onsetcould be chosen. As illustrated in example diagram FIG. 15, a system 910includes implantable medical device (IMD) 916, which is connected toleads 918, 920, and 922, and communicatively coupled to a programmer924. IMD 916 senses electrical signals attendant to the depolarizationand repolarization of heart 912, e.g., a cardiac EGM, via electrodes onone or more of leads 918, 920 and 922 or a housing of IMD 916. IMD 916also delivers therapy in the form of electrical signals to heart 912 viaelectrodes located on one or more leads 918, 920, and 922 or a housingof IMD 916, such pacing, cardioversion and/or defibrillation pulses. IMD916 may include or be coupled to various sensors, such as one or moreaccelerometers, for detecting other physiological parameters of patient914, such as activity or posture.

In some examples, programmer 924 takes the form of a handheld computingdevice, computer workstation, or networked computing device thatincludes a user interface for presenting information to and receivinginput from a user. A user, such as a physician, technician, surgeon,electrophysiologist, or other clinician, may interact with programmer924 to communicate with IMD 916. For example, the user may interact withprogrammer 924 to retrieve physiological or diagnostic information fromIMD 916. A user may also interact with programmer 924 to program IMD916, e.g., select values for operational parameters of the IMD.

IMD 916 and programmer 924 may communicate via wireless communicationusing any techniques known in the art. Examples of communicationtechniques may include, for example, low frequency or radiofrequency(RF) telemetry, but other techniques are also contemplated. In someexamples, programmer 924 may include a programming head that may beplaced proximate to the patient's body near the IMD 916 implant site inorder to improve the quality or security of communication between IMD916 and programmer 924. In other examples, programmer 924 may be locatedremotely from IMD 916, and communicate with IMD 916 via a network.

The techniques for identifying onsets and/or offsets of cardiacelectrogram waves may be performed by IMD 916, e.g., by a processor ofIMD 916, based on one or more cardiac electrograms sensed by the IMD. Inother examples, as described previously, some or all of the functionsascribed to IMD 916 or a processor thereof may be performed by one ormore other devices, such as programmer 294 or a workstation (not shown),or a processor thereof. For example, programmer 924 may process EGMsignals received from IMD 916 and/or cardiac mechanical contractioninformation to according to the techniques described herein.Furthermore, although described herein with respect to an IMD, in otherexamples, the techniques described herein may be performed by orimplemented in an external medical device, which may be coupled to apatient via percutaneous or transcutaneous leads.

FIGS. 16 and 17 are conceptual diagrams illustrating example systems formeasuring body-surface potentials and, more particularly, torso-surfacepotentials. In one example illustrated in FIG. 16, sensing device 1000A,comprising a set of electrodes 1002A-F (generically “electrodes 1002”)and strap 1008, is wrapped around the torso of patient 914 such that theelectrodes surround heart 912. As illustrated in FIG. 16, electrodes1002 may be positioned around the circumference of patient 914,including the posterior, lateral, and anterior surfaces of the torso ofpatient 914. In other examples, electrodes 1002 may be positioned on anyone or more of the posterior, lateral, and anterior surfaces of thetorso. Electrodes 1002 may be electrically connected to a processingunit such as device 60 via wired connection 1004. Some configurationsmay use a wireless connection to transmit the signals sensed byelectrodes 1002 to device 60, e.g., as channels of data.

Although in the example of FIG. 16 sensing device 1000A comprises strap1008, in other examples any of a variety of mechanisms, e.g., tape oradhesives, may be employed to aid in the spacing and placement ofelectrodes 1002. In some examples, strap 1008 may comprise an elasticband, strip of tape, or cloth. In some examples, electrodes 1002 may beplaced individually on the torso of patient 914.

Electrodes 1002 may surround heart 912 of patient 914 and record theelectrical signals associated with the depolarization and repolarizationof heart 912 after the signals have propagated through the torso ofpatient 914. Each of electrodes 1002 may be used in a unipolarconfiguration to sense the torso-surface potentials that reflect thecardiac signals. Device 60 may also be coupled to a return orindifferent electrode (not shown) which may be used in combination witheach of electrodes 1002 for unipolar sensing. In some examples, theremay be 12 to 16 electrodes 1002 spatially distributed around the torsoof patient 914. Other configurations may have more or fewer electrodes1002.

Processing unit 60 may record and analyze the torso-surface potentialsignals sensed by electrodes 1002. As described herein, device 60 may beconfigured to provide an output to a user. The user may make adiagnosis, prescribe CRT, position therapy devices, e.g., leads, oradjust or select treatment parameters based on the indicated output.

In some examples, the analysis of the torso-surface potential signals bydevice 60 may take into consideration the location of electrodes 1002 onthe surface of the torso of patient 914. In such examples, device 60 maybe communicatively coupled to a motion sensing module 80 such as aprogrammer, which may provide an image that allows device 60 todetermine coordinate locations of each of electrodes 1002 on the surfaceof patient 914. Electrodes 1002 may be visible, or made transparentthrough the inclusion or removal of certain materials or elements, inthe image provided by motion sensing module 80.

FIG. 17 illustrates an example configuration of a system that may beused to evaluate cardiac response in heart 912 of patient 914. Thesystem comprises a sensing device 1000B, which may comprise vest 1006and electrodes 1002 A-ZZ (generically “electrodes 1002”), a device 60,and imaging system 501. Device 60 and imaging system 501 may performsubstantially as described above with respect to FIG. 15. As illustratedin FIG. 17, electrodes 1002 are distributed over the torso of patient914, including the anterior, lateral, and posterior surfaces of thetorso of patient 914.

Sensing device 1000B may comprise a fabric vest 1006 with electrodes1002 attached to the fabric. Sensing device 1000B may maintain theposition and spacing of electrodes 1002 on the torso of patient 914.Sensing device 1000B may be marked to assist in determining the locationof electrodes 1002 on the surface of the torso of patient 914. In someexamples, there may be 150 to 256 electrodes 1002 distributed around thetorso of patient 914 using sensing device 1000B, though otherconfigurations may have more or fewer electrodes 1002.

The ECG data is mapped to a generic, graphical model of a patient'storso and/or heart and a graphical display is produced on a graphicaluser interface without taking an actual image, such as an MRI or CTimage, from the patient. The resolution of the ECG data mapped to agraphical anatomical model depends on the number and spacing of surfaceelectrodes 1002 used. In some examples, there may be 12 to 16 electrodesspatially distributed around the torso of patient 914. Each electrode isassociated with a channel that is connected in a processor. Otherconfigurations may have more or fewer electrodes. In one embodiment, aminimum number of electrodes includes twelve electrodes arranged in tworows extending along the posterior torso and twelve electrodes arrangedin two rows extending along the anterior torso for a total oftwenty-four electrodes, which may be equally distributedcircumferentially around the torso. The number of electrodes can begreater than 12 electrodes. In one or more examples presented in methods100-300, 56 channels associated with 56 electrodes are used but skilledartisans will understand that more or less electrodes can be used towith these methods. Another exemplary system with a computing apparatusor processor, electrode apparatus and display apparatus that can be usedis described in U.S. patent application Ser. No. 14/227,955 filed onMar. 27, 2014 entitled SYSTEMS, METHODS, AND INTERFACES FOR IDENTIFYINGEFFECTIVE ELECTRODES, by Ghosh et al. and incorporated by reference inits entirety. Reliable detection of depolarization waves assists thephysician in setting parameters for optimal delivery of CRT.

FIG. 18 is a conceptual diagram illustrating IMD 916 and leads 918, 920,and 922 of system 910 in greater detail. In the illustrated example,bipolar electrodes 940 and 942 are located adjacent to a distal end oflead 918. In addition, bipolar electrodes 944 and 946 are locatedadjacent to a distal end of lead 920, and bipolar electrodes 948 and 950are located adjacent to a distal end of lead 922.

In the illustrated example, electrodes 940, 944 and 948 take the form ofring electrodes, and electrodes 942, 946 and 950 may take the form ofextendable helix tip electrodes mounted retractably within insulativeelectrode heads 952, 954 and 956, respectively. Leads 918, 920, 922 alsoinclude elongated electrodes 962, 964, 966, respectively, which may takethe form of a coil. In some examples, each of the electrodes 940, 942,944, 946, 948, 950, 962, 964 and 966 is electrically coupled to arespective conductor within the lead body of its associated lead 918,920, 922, and thereby coupled circuitry within IMD 916.

In some examples, IMD 916 includes one or more housing electrodes, suchas housing electrode 904 illustrated in FIG. 18, which may be formedintegrally with an outer surface of hermetically-sealed housing 908 ofIMD 916 or otherwise coupled to housing 908. In some examples, housingelectrode 904 is defined by an uninsulated portion of an outward facingportion of housing 908 of IMD 916. Other division between insulated anduninsulated portions of housing 908 may be employed to define two ormore housing electrodes. In some examples, a housing electrode comprisessubstantially all of housing 908.

As described in further detail with reference to FIG. 19, housing 908encloses a signal generator that generates therapeutic stimulation, suchas cardiac pacing, cardioversion and defibrillation pulses, as well as asensing module for sensing electrical signals attendant to thedepolarization and repolarization of heart 912. Housing 908 may alsoenclose a wave detection module that detects the onsets and/or offsetsof heart depolarization and repolarization waves. The wave detectionmodule may be enclosed within housing 908. Alternatively, the wavedetection module may be housed in a remote piece of equipment, such asprogrammer 924 or a workstation (not shown) and communicate with the IMD916 through wireless communication.

IMD 916 senses electrical signals attendant to the depolarization andrepolarization of heart 912 via electrodes 904, 940, 942, 944, 946, 948,950, 962, 964 and 966. IMD 916 may sense such electrical signals via anybipolar combination of electrodes 940, 942, 944, 946, 948, 950, 962, 964and 966. Furthermore, any of the electrodes 940, 942, 944, 946, 948,950, 962, 964 and 966 may be used for unipolar sensing in combinationwith housing electrode 904.

In some examples, IMD 916 delivers pacing pulses via bipolarcombinations of electrodes 940, 942, 944, 946, 948 and 950 to producedepolarization of cardiac tissue of heart 912. In some examples, IMD 16delivers pacing pulses via any of electrodes 940, 942, 944, 946, 948 and950 in combination with housing electrode 904 in a unipolarconfiguration. Furthermore, IMD 916 may deliver cardioversion ordefibrillation pulses to heart 12 via any combination of elongatedelectrodes 962, 964, 966, and housing electrode 904.

The illustrated numbers and configurations of leads 918, 920, and 922and electrodes are merely examples. Other configurations, i.e., numberand position of leads and electrodes, are possible. In some examples,system 910 may include an additional lead or lead segment having one ormore electrodes positioned at different locations in the cardiovascularsystem for sensing and/or delivering therapy to patient 914. Forexample, instead of or in addition to intracardiac leads 918, 920 and922, system 910 may include one or more epicardial or subcutaneous leadsnot positioned within the heart. In some examples, the subcutaneousleads may sense a subcutaneous cardiac electrogram, for example thefar-field electrogram between the SVC coil and the can. The subcutaneouscardiac electrogram may substitute for the surface ECG in determiningthe global electromechanical delay.

FIG. 19 is a block diagram illustrating an example configuration of IMD916. In the illustrated example, IMD 916 includes a processor 970,memory 972, signal generator 974, sensing module 976, telemetry module978, motion sensing module 980, wave detection module 982 and peakdetection module 984. Memory 972 includes computer-readable instructionsthat, when executed by processor 970, causes IMD 916 and processor 970to perform various functions attributed to IMD 916 and processor 970herein. Memory 972 may include any volatile, non-volatile, magnetic,optical, or electrical media, such as a random access memory (RAM),read-only memory (ROM), non-volatile RAM (NVRAM), electrically-erasableprogrammable ROM (EEPROM), flash memory, or any other digital or analogmedia.

Processor 970 may include any one or more of a microprocessor, acontroller, a digital signal processor (DSP), an application specificintegrated circuit (ASIC), a field-programmable gate array (FPGA), orequivalent discrete or analog logic circuitry. In some examples,processor 970 may include multiple components, such as any combinationof one or more microprocessors, one or more controllers, one or moreDSPs, one or more ASICs, or one or more FPGAs, as well as other discreteor integrated logic circuitry. The functions attributed to processor 970herein may be embodied as software, firmware, hardware or anycombination thereof. Generally, processor 970 controls signal generator974 to deliver stimulation therapy to heart 912 of patient 914 accordingto a selected one or more of therapy programs or parameters, which maybe stored in memory 972. As an example, processor 970 may control signalgenerator 974 to deliver electrical pulses with the amplitudes, pulsewidths, frequency, or electrode polarities specified by the selected oneor more therapy programs.

Signal generator 974 is configured to generate and deliver electricalstimulation therapy to patient 912. As shown in FIG. 19, signalgenerator 974 is electrically coupled to electrodes 94, 940, 942, 944,946, 948, 950, 962, 964, and 966, e.g., via conductors of the respectiveleads 918, 920, and 922 and, in the case of housing electrode 904,within housing 908. For example, signal generator 974 may deliverpacing, defibrillation or cardioversion pulses to heart 912 via at leasttwo of electrodes 94, 940, 942, 944, 946, 948, 950, 962, 964, and 966.In other examples, signal generator 974 delivers stimulation in the formof signals other than pulses, such as sine waves, square waves, or othersubstantially continuous time signals.

Signal generator 974 may include a switch module (not shown) andprocessor 970 may use the switch module to select, e.g., via adata/address bus, which of the available electrodes are used to deliverthe electrical stimulation. The switch module may include a switcharray, switch matrix, multiplexer, or any other type of switching devicesuitable to selectively couple stimulation energy to selectedelectrodes. Electrical sensing module 976 monitors electrical cardiacsignals from any combination of electrodes 904, 940, 942, 944, 946, 948,950, 962, 964, and 966. Sensing module 976 may also include a switchmodule which processor 970 controls to select which of the availableelectrodes are used to sense the heart activity, depending upon whichelectrode combination is used in the current sensing configuration.

Sensing module 976 may include one or more detection channels, each ofwhich may comprise an amplifier. The detection channels may be used tosense the cardiac signals. Some detection channels may detect events,such as R-waves or P-waves, and provide indications, such as wavemarkers, of the occurrences of such events to processor 970. One or moreother detection channels may provide the signals to an analog-to-digitalconverter, for conversion into a digital signal for processing oranalysis by processor 970.

For example, sensing module 976 may comprise one or more narrow bandchannels, each of which may include a narrow band filteredsense-amplifier that compares the detected signal to a threshold. If thefiltered and amplified signal is greater than the threshold, the narrowband channel indicates that a certain electrical cardiac event, e.g.,depolarization, has occurred. Processor 970 then uses that detection inmeasuring frequencies of the sensed events.

In one example, at least one narrow band channel may include an R-waveor P-wave amplifier. In some examples, the R-wave and P-wave amplifiersmay take the form of an automatic gain controlled amplifier thatprovides an adjustable sensing threshold as a function of the measuredR-wave or P-wave amplitude. Examples of R-wave and P-wave amplifiers aredescribed in U.S. Pat. No. 5,117,824 to Keimel et al., which issued onJun. 2, 1992 and is entitled, “APPARATUS FOR MONITORING ELECTRICALPHYSIOLOGIC SIGNALS,” and is incorporated herein by reference in itsentirety.

In some examples, sensing module 976 includes a wide band channel whichmay comprise an amplifier with a relatively wider pass band than thenarrow band channels. Signals from the electrodes that are selected forcoupling to this wide-band amplifier may be converted to multi-bitdigital signals by an analog-to-digital converter (ADC) provided by, forexample, sensing module 976 or processor 970. Processor 970 may analyzethe digitized versions of signals from the wide band channel. Processor970 may employ digital signal analysis techniques to characterize thedigitized signals from the wide band channel to, for example, detect andclassify the patient's heart rhythm.

Processor 970 may detect and classify the patient's heart rhythm basedon the cardiac electrical signals sensed by sensing module 976 employingany of the numerous signal processing methodologies known in the art.For example, processor 970 may maintain escape interval counters thatmay be reset upon sensing of R-waves by sensing module 976. The value ofthe count present in the escape interval counters when reset by senseddepolarizations may be used by processor 970 to measure the durations ofR-R intervals, which are measurements that may be stored in memory 972.Processor 970 may use the count in the interval counters to detect atachyarrhythmia, such as ventricular fibrillation or ventriculartachycardia. A portion of memory 972 may be configured as a plurality ofrecirculating buffers, capable of holding series of measured intervals,which may be analyzed by processor 970 to determine whether thepatient's heart 912 is presently exhibiting atrial or ventriculartachyarrhythmia.

In some examples, processor 970 may determine that tachyarrhythmia hasoccurred by identification of shortened R-R interval lengths. Generally,processor 970 detects tachycardia when the interval length falls below360 milliseconds (ms) and fibrillation when the interval length fallsbelow 320 ms. These interval lengths are merely examples, and a user maydefine the interval lengths as desired, which may then be stored withinmemory 972. This interval length may need to be detected for a certainnumber of consecutive cycles, for a certain percentage of cycles withina running window, or a running average for a certain number of cardiaccycles, as examples.

In some examples, an arrhythmia detection method may include anysuitable tachyarrhythmia detection algorithms. In one example, processor970 may utilize all or a subset of the rule-based detection methodsdescribed in U.S. Pat. No. 5,545,186 to Olson et al., entitled,“PRIORITIZED RULE BASED METHOD AND APPARATUS FOR DIAGNOSIS AND TREATMENTOF ARRHYTHMIAS,” which issued on Aug. 13, 1996, or in U.S. Pat. No.5,755,736 to Gillberg et al., entitled, “PRIORITIZED RULE BASED METHODAND APPARATUS FOR DIAGNOSIS AND TREATMENT OF ARRHYTHMIAS,” which issuedon May 26, 1998. U.S. Pat. No. 5,545,186 to Olson et al. U.S. Pat. No.5,755,736 to Gillberg et al. is incorporated herein by reference intheir entireties. However, other arrhythmia detection methodologies mayalso be employed by processor 970 in other examples. For example, EGMmorphology may be considered in addition to or instead of intervallength for detecting tachyarrhythmias.

Generally, processor 970 detects a treatable tachyarrhythmia, such asVF, based on the EGM, e.g., the R-R intervals and/or morphology of theEGM, and selects a therapy to deliver to terminate the tachyarrhythmia,such as a defibrillation pulse of a specified magnitude. The detectionof the tachyarrhythmia may include a number of phases or steps prior todelivery of the therapy, such as first phase, sometimes referred to asdetection, in which a number of consecutive or proximate R-R intervalssatisfies a first number of intervals to detect (NID) criterion, asecond phase, sometimes referred to as confirmation, in which a numberof consecutive or proximate R-R intervals satisfies a second, morerestrictive NID criterion. Tachyarrhythmia detection may also includeconfirmation based on EGM morphology or other sensors subsequent to orduring the second phase.

In the illustrated example, IMD 916 also includes peak detection module980, wave detection module 982, and motion sensing module 984. Peakdetection module 980 and wave detection module 982 may be configured andprovide the functionality ascribed to peak detection module 76 and wavedetection module 78 herein. Peak detection module 980 may be configuredto determine a maximum value of a particular signal. For example, peakdetection module 980 may be configured to receive an electrical signalfrom wave detection module 982 or processor 970 and determine a maximumvalue of the received signal. Peak detection module 980 may, in someexamples, comprise a narrow-band channel of sensing module 976 that isconfigured to detect R-waves, P-waves, or T-waves in cardiac electrogramsignals, e.g., using an amplifier with automatically adjustingthreshold.

Generally, wave detection module 982 determines the onsets and/oroffsets on the heart depolarization and repolarizations waves. Wavedetection module 982 may be similar to the wave detection moduledescribed previously, e.g. wave detection module 78, and more accuratelydescribed in FIG. 2. For example, wave detection module may include alow-pass filter, a window module, a slope module, a rectifier module, asmoothing module, and a threshold detection module. Wave detectionmodule 982 may perform substantially similar to the wave detectionmodule described previously in this application.

Peak detection module 980 and wave detection module 982 may receive acardiac electrogram from sensing module 976, e.g., from a wide-bandchannel of the sensing module. In some examples, the cardiac electrogrammay be a far-field cardiac electrogram, e.g., between superior vena cavacoil 766 and housing electrode 904. Afar-field cardiac electrogram maybe used in the manner described herein with respect to a surface ECG,e.g., to determine a global electromechanical delay. In some examples,the cardiac electrogram may be a unipolar cardiac electrogram betweenhousing electrode 906 and any of electrodes 942, 944, 946 and 950. Theunipolar cardiac electrogram may be received from sensing module 976,e.g., via a wide-band channel of the sensing module, and may be used inthe manner described herein with respect to local cardiac electrogramsignals, e.g., to determine local electromechanical delays.

Motion sensing module 984 may sense the mechanical contraction of theheart, e.g., at one or more cardiac sites. Motion sensing module 984 maybe electrically coupled to one or more sensors that generate a signalthat varies based on cardiac contraction or motion generally, such asone or more accelerometers, pressure sensors, impedance sensors, or flowsensors. The detected contraction may be contraction of cardiac tissueat a particular location, e.g., a particular portion of a ventricularwall.

Although processor 970 and wave detection module 982 are illustrated asseparate modules in FIG. 19, processor 970 and wave detection module 982may be incorporated in a single processing unit. Wave detection module982, and any of its components, may be a component of or module executedby processor 970.

Telemetry module 978 includes any suitable hardware, firmware, softwareor any combination thereof for communicating with another device, suchas programmer 924 (FIG. 15). In some examples, programmer 924 mayinclude a programming head that is placed proximate to the patient'sbody near the IMD 916 implant site, and in other examples programmer 924and IMD 916 may be configured to communicate using a distance telemetryalgorithm and circuitry that does not require the use of a programminghead and does not require user intervention to maintain a communicationlink. Under the control of processor 970, telemetry module 978 mayreceive downlink telemetry from and send uplink telemetry to programmer924 with the aid of an antenna, which may be internal and/or external.In some examples, processor 970 may transmit cardiac signals produced bysensing module 976 and/or signals generated by heart sound sensor 982 toprogrammer 924. Processor 970 may also generate and store marker codesindicative of different cardiac events that sensing module 976 or heartsound analyzer 980 detects, and transmit the marker codes to programmer924. An example IMD with marker-channel capability is described in U.S.Pat. No. 4,374,382 to Markowitz, entitled, “MARKER CHANNEL TELEMETRYSYSTEM FOR A MEDICAL DEVICE,” which issued on Feb. 15, 1983 and isincorporated herein by reference in its entirety. Information whichprocessor 970 may transmit to programmer 924 via telemetry module 978may also include indications of treatable rhythms, and indications ofnon-treatable rhythms in which the EGM based indication indicated thatthe rhythm was treatable and the heart sound based indication indicatedthat the rhythm was non-treatable. Such information may be included aspart of a marker channel with an EGM.

Implementation of the methods disclosed herein requires a plurality ofbody-surface electrodes such as an ECG belt or vest be placed around thetorso of the patient. An exemplary ECG belt or vest is described in U.S.patent application Ser. No. 13/462,404, filed May 2, 2012, entitled“Assessing Infra-Cardiac Activation Patterns And ElectricalDyssynchrony” and assigned to the assignee of the present invention, thedisclosure of which is incorporated by reference in its entirety herein.After the vest or belt is secured around the patient's torso, theprogrammer is activated. Exemplary programmers that can be used toacquire signals from implanted and surface electrodes includes theMedtronic Carelink Programmer Model 2090 and the Model 2290 Analyzer orthe CARELINK ENCORE™. Medtronic Vitatron Reference Manual CARELINKENCORE™ (2013) available from Medtronic.

An exemplary system 1100 can be used to acquire data to determine themost onset of cardiac depolarization and or offset of repolarizationwaves. System 1100 including electrode apparatus 1110, imaging apparatus1120, display apparatus 1130, and computing apparatus 1140 is depictedin FIG. 21. The electrode apparatus 1110 as shown includes a pluralityof electrodes incorporated, or included within a band wrapped around thechest, or torso, of a patient. The electrode apparatus 1110 isoperatively coupled to the computing apparatus 1140 (e.g., through oneor more wired electrical connections, wirelessly, etc.) to provideelectrical signals from each of the electrodes to the computingapparatus 1140 for analysis. Exemplary electrode apparatus may bedescribed in U.S. Provisional Patent Application 61/913,759 entitled“Bioelectric Sensor Device and Methods” and filed on Dec. 9, 2013 andU.S. patent application entitled “Bioelectric Sensor Device and Methods”and filed on even date herewith (Docket No. C00006744.USU2 (134.07930101)), each of which is incorporated herein by reference in itsentirety.

The imaging apparatus 1120 may be any type of imaging apparatusconfigured to image, or provide images of, at least a portion of thepatient in a non-invasive manner. For example, the imaging apparatus1120 may not use any components or parts that may be located within thepatient to provide images of at least a portion of the patient exceptnon-invasive tools such as contrast solution. It is to be understoodthat the exemplary systems, methods, and interfaces described herein maynoninvasively assist a user (e.g., a physician) in selecting a locationproximate a patient's heart for an implantable electrode, and after theexemplary systems, methods, and interfaces have provided noninvasiveassistance, the exemplary systems, methods, and interfaces may thenprovide assistance to implant, or navigate, an implantable electrodeinto the patient, e.g., proximate the patient's heart.

For example, after the exemplary systems, methods, and interfaces haveprovided noninvasive assistance, the exemplary systems, methods, andinterfaces may then provide image guided navigation that may be used tonavigate leads including electrodes, leadless electrodes, wirelesselectrodes, catheters, etc., within the patient's body. Further,although the exemplary systems, methods, and interfaces are describedherein with reference to a patient's heart, it is to be understood thatthe exemplary systems, methods, and interfaces may be applicable to anyother portion of the patient's body.

The imaging apparatus 1120 may be configured to capture, or take, x-rayimages (e.g., two dimensional x-ray images, three dimensional x-rayimages, etc.) of the patient. The imaging apparatus 1120 may beoperatively coupled (e.g., through one or more wired electricalconnections, wirelessly, etc.) to the computing apparatus 140 such thatthe images captured by the imaging apparatus 1120 may be transmitted tothe computing apparatus 1140. Further, the computing apparatus 1140 maybe configured to control the imaging apparatus 1120 to, e.g., configurethe imaging apparatus 1120 to capture images, change one or moresettings of the imaging apparatus 1120, etc.

It will be recognized that while the imaging apparatus 1120 as shown inFIG. 21 may be configured to capture x-ray images, any other alternativeimaging modality may also be used by the exemplary systems, methods, andinterfaces described herein. For example, the imaging apparatus 1120 maybe configured to capture images, or image data, using isocentricfluoroscopy, bi-plane fluoroscopy, ultrasound, computed tomography (CT),multi-slice computed tomography (MSCT), magnetic resonance imaging(MRI), high frequency ultrasound (HIFU), optical coherence tomography(OCT), intra-vascular ultrasound (IVUS), two dimensional (2D)ultrasound, three dimensional (3D) ultrasound, four dimensional (4D)ultrasound, intraoperative CT, intraoperative MRI, etc. Further, it isto be understood that the imaging apparatus 120 may be configured tocapture a plurality of consecutive images (e.g., continuously) toprovide video frame data. In other words, a plurality of images takenover time using the imaging apparatus 120 may provide motion picturedata. Additionally, the images may also be obtained and displayed intwo, three, or four dimensions. In more advanced forms, four-dimensionalsurface rendering of the heart or other regions of the body may also beachieved by incorporating heart data or other soft tissue data from anatlas map or from pre-operative image data captured by MRI, CT, orechocardiography modalities. Image datasets from hybrid modalities, suchas positron emission tomography (PET) combined with CT, or single photonemission computer tomography (SPECT) combined with CT, could alsoprovide functional image data superimposed onto anatomical data to beused to confidently reach target locations within the heart or otherareas of interest.

The display apparatus 1130 and the computing apparatus 140 may beconfigured to display and analyze data such as, e.g., surrogateelectrical activation data, image data, mechanical motion data, etc.gathered, or collected, using the electrode apparatus 1110 and theimaging apparatus 1120 to noninvasively assist a user in locationselection of an implantable electrode. In at least one embodiment, thecomputing apparatus 140 may be a server, a personal computer, or atablet computer. The computing apparatus 140 may be configured toreceive input from input apparatus 1142 and transmit output to thedisplay apparatus 1130. Further, the computing apparatus 1140 mayinclude data storage that may allow for access to processing programs orroutines and/or one or more other types of data, e.g., for driving agraphical user interface configured to noninvasively assist a user inlocation selection of an implantable electrode, etc.

The computing apparatus 1140 may be operatively coupled to the inputapparatus 1142 and the display apparatus 1130 to, e.g., transmit data toand from each of the input apparatus 1142 and the display apparatus1130. For example, the computing apparatus 1140 may be electricallycoupled to each of the input apparatus 1142 and the display apparatus1130 using, e.g., analog electrical connections, digital electricalconnections, wireless connections, bus-based connections, network-basedconnections, internet-based connections, etc. As described furtherherein, a user may provide input to the input apparatus 1142 tomanipulate, or modify, one or more graphical depictions displayed on thedisplay apparatus 1130 to view and/or select one or more target orcandidate locations of a portion of a patient's heart as furtherdescribed herein.

Although as depicted the input apparatus 1142 is a keyboard, it is to beunderstood that the input apparatus 1142 may include any apparatuscapable of providing input to the computing apparatus 1140 to performthe functionality, methods, and/or logic described herein. For example,the input apparatus 1142 may include a mouse, a trackball, a touchscreen(e.g., capacitive touchscreen, a resistive touchscreen, a multi-touchtouchscreen, etc.), etc. Likewise, the display apparatus 1130 mayinclude any apparatus capable of displaying information to a user, suchas a graphical user interface 132 including graphical depictions ofanatomy of a patient's heart, images of a patient's heart, graphicaldepictions of locations of one or more electrodes, graphical depictionsof one or more target or candidate locations, alphanumericrepresentations of one or more values, graphical depictions or actualimages of implanted electrodes and/or leads, etc. For example, thedisplay apparatus 1130 may include a liquid crystal display, an organiclight-emitting diode screen, a touchscreen, a cathode ray tube display,etc.

The graphical user interfaces 1132 displayed by the display apparatus130 may include, or display, one or more regions used to displaygraphical depictions, to display images, to allow selection of one ormore regions or areas of such graphical depictions and images, etc. Asused herein, a “region” of a graphical user interface 1132 may bedefined as a portion of the graphical user interface 1132 within whichinformation may be displayed or functionality may be performed. Regionsmay exist within other regions, which may be displayed separately orsimultaneously. For example, smaller regions may be located withinlarger regions, regions may be located side-by-side, etc. Additionally,as used herein, an “area” of a graphical user interface 1132 may bedefined as a portion of the graphical user interface 1132 located with aregion that is smaller than the region it is located within. Exemplarysystems and interfaces may be described in U.S. Provisional PatentApplication 61/913,743 entitled “Noninvasive Cardiac Therapy Evaluation”and filed on Dec. 9, 2013 and U.S. patent application entitled“Noninvasive Cardiac Therapy Evaluation” and filed on even date herewith(Docket No. C00006745.USU2 (134.0794 0101)), each of which isincorporated herein by reference in its entirety.

The processing programs or routines stored and/or executed by thecomputing apparatus 1140 may include programs or routines forcomputational mathematics, matrix mathematics, decomposition algorithms,compression algorithms (e.g., data compression algorithms), calibrationalgorithms, image construction algorithms, signal processing algorithms(e.g., Fourier transforms, fast Fourier transforms, etc.),standardization algorithms, comparison algorithms, vector mathematics,or any other processing required to implement one or more exemplarymethods and/or processes described herein. Data stored and/or used bythe computing apparatus 1140 may include, for example, image data fromthe imaging apparatus 1120, electrical signal data from the electrodeapparatus 1110, graphics (e.g., graphical elements, icons, buttons,windows, dialogs, pull-down menus, graphic areas, graphic regions, 3Dgraphics, etc.), graphical user interfaces, results from one or moreprocessing programs or routines employed according to the disclosureherein, or any other data that may be necessary for carrying out the oneand/or more processes or methods described herein.

Far-field EGMs, ECG, or ECG-like signals are acquired from an electrodethat is the greatest distance away from the pacing electrode. If an IMDis implanted, electrodes that can produce far field signals includesuperior vena cava (SVC) electrode-pulse generator housing (alsoreferred to as a “can”), right ventricle (RV) coil-can etc.).

Additionally, pre-specified windows can be defined as extending from theatrial marker to the ventricular marker.

A low pass filter is then applied to the ECG signal within thepre-specified window. The low-pass filter can be a Bessel filter with acut-off frequency of 15 Hz, 20 Hz or a frequency value between 15 Hz and20 Hz. The signal(s) acquired from the plurality of surface electrodesand/or the electrodes associated with the implantable medical device ispassed through the low pass filter, which causes the removal of anyspurious high-frequency artifacts or components from the far-fieldECG-like signal.

A rectified slope of the signal within the window is determined at block1108 using module 96 depicted in FIG. 2. Rectification of a signal canbe performed by any known method.

The techniques described in this disclosure, including those attributedto IMD wave detection module 80, programmer 24, or various constituentcomponents, may be implemented, at least in part, in hardware, software,firmware or any combination thereof. For example, various aspects of thetechniques may be implemented within one or more processors, includingone or more microprocessors, digital signal processors (DSPs),application specific integrated circuits (ASICs), field programmablegate arrays (FPGAs), or any other equivalent integrated or discretelogic circuitry, as well as any combinations of such components,embodied in programmers, such as physician or patient programmers,stimulators, image processing devices or other devices. The term“processor” or “processing circuitry” may generally refer to any of theforegoing logic circuitry, alone or in combination with other logiccircuitry, or any other equivalent circuitry.

Such hardware, software, firmware may be implemented within the samedevice or within separate devices to support the various operations andfunctions described in this disclosure. In addition, any of thedescribed units, modules or components may be implemented together orseparately as discrete but interoperable logic devices. Depiction ofdifferent features as modules or units is intended to highlightdifferent functional aspects and does not necessarily imply that suchmodules or units must be realized by separate hardware or softwarecomponents. Rather, functionality associated with one or more modules orunits may be performed by separate hardware or software components, orintegrated within common or separate hardware or software components.Additionally, skilled artisans understand that the system and/or methodautomatically store any result from a calculation or determination.

There are a variety of other embodiments that can be employed for thepre-specified window used in FIG. 15. For example, the pre-specifiedwindow can be set to begin at an atrial wave marker and extend a certainlength of time or to another marker. In yet another embodiment, thepre-specified window can be set to begin at a ventricular wave markerand extend a certain length of time or to another marker.

Exemplary systems that can be employ one or more methods describedherein include U.S. Pat. No. 8,887,736, U.S. Pat. No. 8,532,734B2, U.S.Pat. No. 8,457,371 B2, U.S. Pat. No. 8,442,625B2, U.S. Pat. No.8,424,536B2, U.S. Pat. No. 8,421,799B2, U.S. Pat. No. 8,391,965B2, U.S.Pat. No. 8,364,252B2, U.S. Pat. No. 8,345,067B2, US20120130232A1, U.S.Pat. No. 8,185,192B2, U.S. Pat. No. 8,106,905B2, US20090265128A1,US20090264751A1, US20090264750A1, US20090264749A1, US20090264748A1,US20090264747A1, US20090264746A1, US20090264727A1, US20090262992A1,US20090262109A1, U.S. Pat. No. 8,843,189B2, U.S. Pat. No. 8,839,798B2,U.S. Pat. No. 8,839,798B2, U.S. Pat. No. 8,663,120B2, U.S. Pat. No.8,660,640B2, U.S. Pat. No. 8,560,042B2, U.S. Pat. No. 8,494,608B2, U.S.Pat. No. 8,340,751B2, U.S. Pat. No. 8,260,395B2, US20120190993A1, U.S.Pat. No. 8,214,018B2, U.S. Pat. No. 8,208,991B2, US20090297001A1,US20090264777A1, US20090264752A1, US20090264743A1, US20090264742A1, U.S.Pat. No. 8,831,701B2, U.S. Pat. No. 8,494,614B2, US20100004724A1, U.S.Pat. No. 6,263,235 B1 all of which are incorporated by reference intheir entirety.

Exemplary embodiments are as follows:

-   -   Embodiment 1 is system for use in monitoring cardiac signals        comprising:    -   an electrode apparatus comprising a plurality of electrodes        configured to be located proximate tissue of a patient;        -   a display apparatus comprising a graphical user interface,            wherein the graphical user interface is configured to            present information for use in assisting a user in            determining whether a signal is ambiguous;        -   computing apparatus coupled to the electrode apparatus and            display apparatus, wherein the computing apparatus is            configured to determine whether a signal acquired from a            channel associated with an electrode is ambiguous, the            computing apparatus configured to:        -   i) calculate a first derivative of the signal;        -   ii) determine a first minimum derivative from the first            derivative;        -   iii) determine a second minimum derivative and a second            index within a window;        -   iv) calculate a ratio of the first and second minimum            derivatives;        -   v) calculate a difference between a first and second index;            and        -   in response to determining the ratio and the difference            between the first and second index, displaying on the            display apparatus whether the signal is ambiguous.    -   Embodiment 2 is a system according to embodiment 1 wherein in        response to determining the difference between the first and        second index is less than a preselected number, the signal is        indicated as potentially ambiguous.    -   Embodiment 3 is a system according to embodiments 1 or 2 wherein        the signal is confirmed as being ambiguous in response to        determining that the ratio is less than a preselected number.    -   Embodiment 4 is a system according to embodiments 1 through 3        wherein the signal is confirmed as being ambiguous in response        to determining that the ratio is greater than a preselected        number.    -   Embodiment 5 is a system according to embodiments 1 through 4        wherein in response to determining the difference between the        first and second index being greater or equal to a preselected        number, the signal being indicated as non-ambiguous.    -   Embodiment 6 is a system according to embodiments 2 through 5        wherein the signal is non-ambiguous in response to determining        that the ratio is greater than or equal to a preselected number.    -   Embodiment 7 is a system of embodiments 1-6 wherein the        electrode apparatus is located around the patient's torso.    -   Embodiment 8 is the system of embodiments 1-7 wherein        determining whether a signal is ambiguous occurs during ablation        of human tissue.    -   Embodiment 9 is the system of embodiments 1-8 wherein the signal        is acquired from a patient diagnosed with atrial fibrillation.    -   Embodiment 10 is the system of embodiments 1-9 wherein the        system is used to locate optimal electrode placement for cardiac        therapy.    -   Embodiment 11 is a method for a multichannel mapping system        comprising a processor connected to an electrode apparatus and a        display apparatus, the electrode apparatus located proximate        tissue of a patient, wherein the processor is configured to        determine whether a signal is ambiguous, the method comprising:        -   acquiring a signal by the processor from an electrode            associated with an electrode apparatus, the processor            executing a set of instructions comprising:        -   i) calculating a first derivative of the signal;        -   iii) determining a minimum and maximum derivative from the            first derivative;        -   iii) determining first and second minimum derivatives and            their respective first and second index within a window;        -   iv) calculating a ratio of the first and second minimum            derivatives;        -   v) calculating a difference between a first and second            index; and        -   in response to determining the ratio and the difference            between the first and second index, displaying on the            display apparatus whether the signal is ambiguous.    -   Embodiment 12 is a method according to embodiment 11 wherein in        response to determining the difference between the first and        second index being less than a preselected number, the signal        being indicated as potentially ambiguous.    -   Embodiment 13 is a method according to embodiment 12 wherein the        signal is confirmed as being ambiguous in response to        determining that the ratio is less than a preselected number.    -   Embodiment 14 is a method according to embodiment 12 wherein the        signal is confirmed as being ambiguous in response to        determining that the ratio is greater than a preselected number.    -   Embodiment 15 is a method according to embodiment 11 wherein in        response to determining the difference between the first and        second index being greater or equal to a preselected number, the        signal being indicated as non-ambiguous.    -   Embodiment 16 is a method according to embodiment 12 wherein the        signal is non-ambiguous in response to determining that the        ratio is greater than or equal to a preselected number.    -   Embodiment 17 is the method of embodiments 11-16 wherein the        electrode apparatus is located around the patient's torso.    -   Embodiment 18 is the method of embodiments 11-17 wherein        determining whether a signal is ambiguous occurs during ablation        of human tissue.    -   Embodiment 19 is the method of embodiments 11-18 wherein the        signal is acquired from a patient diagnosed with atrial        fibrillation.    -   Embodiment 20 is the method of embodiments 11-19 wherein the        system is used to locate optimal electrode placement for cardiac        therapy.    -   Embodiment 21 is a system for use in monitoring cardiac signals        comprising:        -   an electrode located proximate cardiac tissue of a patient;        -   display apparatus comprising a graphical user interface,            wherein the graphical user interface is configured to            present information for use in assisting a user in            determining whether a signal is ambiguous;        -   computing apparatus coupled to the electrode and display            apparatus, wherein the computing apparatus is configured to            determine whether a signal acquired from a channel            associated with an electrode is ambiguous, the computing            apparatus configured to        -   determine whether the signal is ambiguous based solely on a            derivative of the signal and index data.    -   Embodiment 23 is a machine readable medium containing executable        computer program instructions which when executed by a data        processing system cause said system to perform a method of        displaying cardiac signals, the method comprising:        -   acquiring a signal by the processor from an electrode            associated with an electrode apparatus, the processor            executing a set of instructions comprising:        -   ii) calculating a first derivative of the signal;        -   iv) determining a minimum and maximum derivative from the            first derivative;        -   iii) determining first and second minimum derivatives and            their respective first and second index within a window;        -   iv) calculating a ratio of the first and second minimum            derivatives;        -   v) calculating a difference between a first and second            index; and        -   in response to determining the ratio and the difference            between the first and second index, displaying on the            display apparatus whether the signal is ambiguous.

When implemented in software, the functionality ascribed to the systems,devices and techniques described in this disclosure may be embodied asinstructions on a computer-readable medium such as random access memory(RAM), read-only memory (ROM), non-volatile random access memory(NVRAM), electrically erasable programmable read-only memory (EEPROM),FLASH memory, magnetic data storage media, optical data storage media,or the like. The instructions may be executed to support one or moreaspects of the functionality described in this disclosure.

1. A system for use in monitoring cardiac signals comprising: anelectrode apparatus comprising a plurality of electrodes configured tobe located proximate tissue of a patient; a display apparatus comprisinga graphical user interface, wherein the graphical user interface isconfigured to present information for use in assisting a user indetermining whether a signal is ambiguous; computing apparatus coupledto the electrode apparatus and display apparatus, wherein the computingapparatus is configured to determine whether a signal acquired from achannel associated with an electrode is ambiguous, the computingapparatus configured to: v) calculate a first derivative of the signal;vi) determine a first minimum derivative from the first derivative; iii)determine a second minimum derivative and a second index within awindow; iv) calculate a ratio of the first and second minimumderivatives; v) calculate a difference between a first and second index;and in response to determining the ratio and the difference between thefirst and second index, displaying on the display apparatus whether thesignal is ambiguous.
 2. A system according to claim 1 wherein inresponse to determining the difference between the first and secondindex is less than a preselected number, the signal is indicated aspotentially ambiguous.
 3. A system according to claim 2 wherein thesignal is confirmed as being ambiguous in response to determining thatthe ratio is less than a preselected number.
 4. A system according toclaim 2 wherein the signal is confirmed as being ambiguous in responseto determining that the ratio is greater than a preselected number.
 5. Asystem according to claim 1 wherein in response to determining thedifference between the first and second index being greater or equal toa preselected number, the signal being indicated as non-ambiguous.
 6. Asystem according to claim 2 wherein the signal is non-ambiguous inresponse to determining that the ratio is greater than or equal to apreselected number.
 7. The system of claim 1 wherein the electrodeapparatus is located around the patient's torso.
 8. The system of claim1 wherein determining whether a signal is ambiguous occurs duringablation of human tissue.
 9. The system of claim 1 wherein the signal isacquired from a patient diagnosed with atrial fibrillation.
 10. Thesystem of claim 1 wherein the system is used to locate optimal electrodeplacement for cardiac therapy.
 11. A method for a multichannel mappingsystem comprising a processor connected to an electrode apparatus and adisplay apparatus, the electrode apparatus located proximate tissue of apatient, wherein the processor is configured to determine whether asignal is ambiguous, the method comprising: acquiring a signal by theprocessor from an electrode associated with an electrode apparatus, theprocessor executing a set of instructions comprising: iii) calculating afirst derivative of the signal; vii) determining a minimum and maximumderivative from the first derivative; iii) determining first and secondminimum derivatives and their respective first and second index within awindow; iv) calculating a ratio of the first and second minimumderivatives; v) calculating a difference between a first and secondindex; and in response to determining the ratio and the differencebetween the first and second index, displaying on the display apparatuswhether the signal is ambiguous.
 12. A method according to claim 11wherein in response to determining the difference between the first andsecond index being less than a preselected number, the signal beingindicated as potentially ambiguous.
 13. A method according to claim 12wherein the signal is confirmed as being ambiguous in response todetermining that the ratio is less than a preselected number.
 14. Amethod according to claim 12 wherein the signal is confirmed as beingambiguous in response to determining that the ratio is greater than apreselected number.
 15. A method according to claim 11 wherein inresponse to determining the difference between the first and secondindex being greater or equal to a preselected number, the signal beingindicated as non-ambiguous.
 16. A method according to claim 12 whereinthe signal is non-ambiguous in response to determining that the ratio isgreater than or equal to a preselected number.
 17. The method of claim11 wherein the electrode apparatus is located around the patient'storso.
 18. The method of claim 11 wherein determining whether a signalis ambiguous occurs during ablation of human tissue.
 19. The method ofclaim 11 wherein the signal is acquired from a patient diagnosed withatrial fibrillation.
 20. The method of claim 11 wherein the system isused to locate optimal electrode placement for cardiac therapy.
 21. Asystem for use in monitoring cardiac signals comprising: an electrodelocated proximate cardiac tissue of a patient; display apparatuscomprising a graphical user interface, wherein the graphical userinterface is configured to present information for use in assisting auser in determining whether a signal is ambiguous; computing apparatuscoupled to the electrode and display apparatus, wherein the computingapparatus is configured to determine whether a signal acquired from achannel associated with an electrode is ambiguous, the computingapparatus configured to determine whether the signal is ambiguous basedsolely on a derivative of the signal and index data.
 22. A machinereadable medium containing executable computer program instructionswhich when executed by a data processing system cause said system toperform a method of displaying cardiac signals, the method comprising:acquiring a signal by the processor from an electrode associated with anelectrode apparatus, the processor executing a set of instructionscomprising: iv) calculating a first derivative of the signal; viii)determining a minimum and maximum derivative from the first derivative;iii) determining first and second minimum derivatives and theirrespective first and second index within a window; iv) calculating aratio of the first and second minimum derivatives; v) calculating adifference between a first and second index; and in response todetermining the ratio and the difference between the first and secondindex, displaying on the display apparatus whether the signal isambiguous.
 23. A method for a multichannel mapping system comprising aprocessor connected to an electrode apparatus and a display apparatus,the electrode apparatus located proximate tissue of a patient, whereinthe processor is configured to determine whether a signal is ambiguous,the method comprising: acquiring a signal by the processor from anelectrode associated with an electrode apparatus, the processorexecuting a set of instructions comprising: v) calculating a firstderivative of the signal; ix) determining a minimum and maximum from thefirst derivative; iii) determining first and second minimum of the firstderivative and their respective first and second index within a window;iv) calculating a ratio of the first and second minimum of the firstderivative; v) calculating a difference between a first and secondindex; and in response to determining the ratio and the differencebetween the first and second index, displaying on the display apparatuswhether the signal is ambiguous.